Name: Satellite Remote Sensing Data Bootcamp With Opensource Tools
Price: 33.99 GBP
Availability: InStock

<div id="course-pills-1">Duration<p>1 Days</p><p>6 CPD hours</p>This course is intended for<p>This introductory-level course is great for experienced technical professionals working in a wide range of industries, such as software development, data science, marketing and advertising, finance, healthcare, and more, who are looking to use the latest AI and machine learning techniques in their day to day. The hands-on labs in this course use Python, so you should have some familiarity with Python scripting basics.</p>Overview<p>Working in an interactive learning environment, led by our engaging OpenAI expert you'll:<br />Understand the capabilities and products offered by OpenAI and how to access them through the OpenAI API.<br />set up an OpenAI environment on Azure, including creating an Azure virtual machine and configuring the environment to connect to Azure resources.<br />Gain hands-on experience building a GPT-3 based chatbot on Azure and implement advanced natural language processing capabilities.<br />Use the OpenAI API to access GPT-3 and generate high-quality text<br />Learn how to use Whisper to improve the quality of text generation.<br />Understand the capabilities of DALL-E and use it to generate images for unique and engaging visuals.</p><p>Geared for technical professionals, Quick Start to Azure AI Basics for Technical Users is a fun, fast paced course designed to quickly get you up to speed with OpenAI?s powerful tools and functionality, and to provide hands-on experience in setting up an OpenAI environment on Azure. Guided by our AI expert, you?ll explore the capabilities of OpenAI's GPT-3, Whisper and DALL-E, and build a chatbot on Azure. It will provide you with the knowledge and resources to continue your journey in AI and machine learning and have a good understanding of the potential of OpenAI and Azure for your projects. First, you?ll dive into the world of OpenAI, learning about its products and the capabilities they offer. You'll also discover how Azure's offerings for AI and machine learning can complement OpenAI's tools and resources, providing you with a powerful combination for your projects. And don't worry if you're new to Azure, we'll walk you through the process of setting up an account and creating a resource group. As you progress through the course, you'll get the chance to work with OpenAI's GPT-3, one of the most advanced large language models available today. You'll learn how to use the OpenAI API to access GPT-3 and discover how to use it to generate high-quality text quickly and easily. And that's not all, you'll also learn how to build a GPT-3 based chatbot on Azure, giving you the opportunity to implement advanced natural language processing capabilities in your chatbot projects. The course will also cover OpenAI Whisper, an OpenAI tool that can improve the quality of text generation, allowing you to create more coherent and natural language content. And you will learn about OpenAI DALL-E, an OpenAI tool that can generate images, giving you the ability to create unique and engaging visuals to enhance your content and projects.</p></div><div id="course-pills-2"><h4>Introduction to OpenAI and Azure</h4><ul><li>Explore OpenAI and its products, as well as Azure's offerings for AI and Machine Learning, allowing you to understand the tools and resources available to you for your AI projects. </li><li>Explore OpenAI and its products </li><li>Explore Azure and its offerings for AI and Machine Learning </li></ul><h4>Get Hands-On: Setting up an OpenAI environment on  Azure</h4><ul><li>Walk through the process of setting up an OpenAI environment on Azure, giving you the hands-on experience needed to start building your own projects using OpenAI and Azure. </li><li>Create an Azure virtual machine and installing the OpenAI SDK </li><li>Configure the OpenAI environment and connecting to Azure resources</li></ul><h4>Explore OpenAI GPT-3 </h4><ul><li>Learn about GPT-3, one of OpenAI's most powerful language models, and how to use it to generate high quality text, giving you the ability to create natural language content quickly and easily. </li><li>Review GPT-3 and its capabilities </li><li>Use the OpenAI API to access GPT-3 </li></ul><h4>Get Hands-on: Building a GPT-3 based chatbot on Azure</h4><ul><li>Learn how to build a GPT-3 based chatbot on Azure, giving you the opportunity to learn how to implement advanced natural language processing capabilities in your chatbot projects. </li><li>Setup an Azure Function and creating a chatbot </li><li>Integrate GPT-3 with the chatbot</li></ul><h4>OpenAI Whisper</h4><ul><li>Explore Whisper, an OpenAI tool that can improve the quality of text generation, allowing you to create more coherent and natural language content. </li><li>Explore Whisper and its capabilities </li><li>Use Whisper to improve the quality of text generation</li></ul><h4>OpenAI DALL-E</h4><ul><li>Explore DALL-E, an OpenAI tool that can generate images, giving you the ability to create unique and engaging visuals to enhance your content and projects. </li><li>Explore DALL-E and its capabilities </li><li>Use the OpenAI API to access DALL-E </li></ul><h4>What?s Next: Keep Going! </h4><ul><li>Other ways OpenAI can impact your day to day </li><li>Explore great places to check for expanded tools and add-ons for Azure OpenAI </li><li>Where to go for help and support</li></ul><h4>Quick Look at Generative AI and its Business  Implications</h4><ul><li>Understanding Generative AI </li><li>Generative AI in Business </li><li>Ethical considerations of Generative AI </li></ul></div>

Nexus Human

Generative AI

NLP Practitioner

Microsoft Azure

Azure Machine Learning

Azure Cognitive Services

AI (Artificial Intelligence)

Quick Start to Using Azure AI for Technical Users (TTAI2330)

Packt

DevOps

Kubernetes

Docker

Jenkins

This course will teach you the fundamentals of Jenkins and how to continually implement and deploy codes in a DevOps environment. You will also learn how to integrate automated tests to verify the build pipelines and set up code quality reporting.

CI/CD Pipelines with Jenkins Certification Training Course

General Admission

<p>Do you want to master the essential mathematical skills for data science and machine learning? Do you want to learn how to apply statistics and probability to real-world problems and scenarios? If yes, then this course is for you!</p>
<p>In this course, you will learn the advanced concepts and techniques of statistics and probability that are widely used in data science and machine learning. You will learn how to describe and analyse data using descriptive statistics, distributions, and probability theory. You will also learn how to perform hypothesis testing, regressions, ANOVA, and machine learning algorithms to make predictions and inferences from data. You will gain hands-on experience with practical exercises and projects using Python and R.</p>
<p><strong>Learning Outcomes</strong></p>
<p>By the end of this course, you will be able to:</p>
<ul>
<li>Apply descriptive statistics, distributions, and probability theory to summarise and visualise data</li>
<li>Perform hypothesis testing, regressions, ANOVA, and machine learning algorithms to make predictions and inferences from data</li>
<li>Use Python and R to implement statistical and machine learning methods</li>
<li>Interpret and communicate the results of your analysis using appropriate metrics and visualisations</li>
<li>Solve real-world problems and scenarios using statistics and probability</li>
</ul>
<h3><b>Why choose this Advanced Diploma in Statistics &amp; Probability for Data Science &amp; Machine Learning at QLS Level 7<span> course</span>?</b></h3>
<ol>
<li>Unlimited access to the course for a lifetime.</li>
<li>Opportunity to earn a certificate accredited by the <b>CPD Quality Standards</b> and <b>CIQ </b>after completing this course.</li>
<li>Structured lesson planning in line with industry standards.</li>
<li>Immerse yourself in innovative and captivating course materials and activities.</li>
<li>Assessments designed to evaluate advanced cognitive abilities and skill proficiency.</li>
<li>Flexibility to complete the Course at your own pace, on your own schedule.</li>
<li>Receive full tutor support throughout the week, from Monday to Friday, to enhance your learning experience.</li>
<li>Unlock career resources for CV improvement, interview readiness, and job success.</li>
</ol>
<h3><b>Who is this Advanced Diploma in Statistics &amp; Probability for Data Science &amp; Machine Learning at QLS Level 7<span> </span></b><b><span>course </span></b><b>for?</b></h3>
<p>This course is for anyone who wants to learn the advanced concepts and techniques of statistics and probability for data science and machine learning. This course is suitable for:</p>
<ul>
<li>Data scientists, machine learning engineers, and analysts who want to enhance their skills and knowledge</li>
<li>Students and researchers who want to learn the mathematical foundations of data science and machine learning</li>
<li>Professionals and managers who want to understand and apply data-driven decision making</li>
<li>Hobbyists and enthusiasts who want to explore and learn from data</li>
<li>Anyone who loves statistics and probability and wants to challenge themselves</li>
</ul>
<h3><b>Career path</b></h3>
<ul>
<li><strong>Data Scientist</strong> (£35,000 - £55,000)</li>
<li><strong>Machine Learning Engineer</strong> (£40,000 - £60,000)</li>
<li><strong>Statistician</strong> (£35,000 - £55,000)</li>
<li><strong>Data Analyst</strong> (£40,000 - £60,000)</li>
<li><strong>Business Intelligence</strong> <strong>Analyst</strong> (£45,000 - £65,000)</li>
<li><strong>Senior Data Analyst</strong> (£50,000 - £70,000)</li>
</ul>
<h3><b>Prerequisites</b></h3>
<p><span>This </span><b>Advanced Diploma in Statistics &amp; Probability for Data Science &amp; Machine Learning at QLS Level 7</b><span> does not require you to have any prior qualifications or experience. You can just enrol and start learning.This </span><b>Advanced Diploma in Statistics &amp; Probability for Data Science &amp; Machine Learning at QLS Level 7</b><span> was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection.</span></p>
<h3><b>Certification</b></h3>
<p><span>After studying the course materials, there will be a written assignment test which you can take at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £4.99 Original Hard Copy certificates need to be ordered at an additional cost of £8.</span></p>
<p><b>Endorsed Certificate of Achievement from the Quality Licence Scheme</b></p>
<p>Learners will be able to achieve an endorsed certificate after completing the course as proof of their achievement. You can order the endorsed certificate for only £135 to be delivered to your home by post. For international students, there is an additional postage charge of £10.</p>
<p><b>Endorsement</b></p>
<p>The Quality Licence Scheme (QLS) has endorsed this course for its high-quality, non-regulated provision and training programmes. The QLS is a UK-based organisation that sets standards for non-regulated training and learning. This endorsement means that the course has been reviewed and approved by the QLS and meets the highest quality standards.</p>
<p>Please Note: Studyhub is a Compliance Central approved resale partner for Quality Licence Scheme Endorsed courses.</p><div>
				<h3>
	<span>Course Curriculum</span>
</h3>

<div>
<table width="100%">				<tbody><tr>
					<td colspan="4">Section 01: Let's get started</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Welcome!</td>
					<td> </td>
					<td><span><i></i> 00:02:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>What will you learn in this course?</td>
					<td> </td>
					<td><span><i></i> 00:06:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>How can you get the most out of it?</td>
					<td> </td>
					<td><span><i></i> 00:06:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Section 02: Descriptive statistics</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Intro</td>
					<td> </td>
					<td><span><i></i> 00:03:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Mean</td>
					<td> </td>
					<td><span><i></i> 00:06:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Median</td>
					<td> </td>
					<td><span><i></i> 00:05:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Mode</td>
					<td> </td>
					<td><span><i></i> 00:04:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Mean or Median?</td>
					<td> </td>
					<td><span><i></i> 00:08:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Skewness</td>
					<td> </td>
					<td><span><i></i> 00:08:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Practice: Skewness</td>
					<td> </td>
					<td><span><i></i> 00:01:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Solution: Skewness</td>
					<td> </td>
					<td><span><i></i> 00:03:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Range &amp; IQR</td>
					<td> </td>
					<td><span><i></i> 00:10:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Sample vs. Population</td>
					<td> </td>
					<td><span><i></i> 00:05:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Variance &amp; Standard deviation</td>
					<td> </td>
					<td><span><i></i> 00:11:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Impact of Scaling &amp; Shifting</td>
					<td> </td>
					<td><span><i></i> 00:19:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Statistical moments</td>
					<td> </td>
					<td><span><i></i> 00:06:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Section 03: Distributions</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>What is a distribution?</td>
					<td> </td>
					<td><span><i></i> 00:10:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Normal distribution</td>
					<td> </td>
					<td><span><i></i> 00:09:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Z-Scores</td>
					<td> </td>
					<td><span><i></i> 00:13:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Practice: Normal distribution</td>
					<td> </td>
					<td><span><i></i> 00:04:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Solution: Normal distribution</td>
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Section 04: Probability theory</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Intro</td>
					<td> </td>
					<td><span><i></i> 00:01:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Probability Basics</td>
					<td> </td>
					<td><span><i></i> 00:10:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Calculating simple Probabilities</td>
					<td> </td>
					<td><span><i></i> 00:05:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Practice: Simple Probabilities</td>
					<td> </td>
					<td><span><i></i> 00:01:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Quick solution: Simple Probabilities</td>
					<td> </td>
					<td><span><i></i> 00:01:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Detailed solution: Simple Probabilities</td>
					<td> </td>
					<td><span><i></i> 00:06:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Rule of addition</td>
					<td> </td>
					<td><span><i></i> 00:13:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Practice: Rule of addition</td>
					<td> </td>
					<td><span><i></i> 00:02:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Quick solution: Rule of addition</td>
					<td> </td>
					<td><span><i></i> 00:01:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Detailed solution: Rule of addition</td>
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Rule of multiplication</td>
					<td> </td>
					<td><span><i></i> 00:11:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Practice: Rule of multiplication</td>
					<td> </td>
					<td><span><i></i> 00:01:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Solution: Rule of multiplication</td>
					<td> </td>
					<td><span><i></i> 00:03:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Bayes Theorem</td>
					<td> </td>
					<td><span><i></i> 00:10:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Bayes Theorem - Practical example</td>
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Expected value</td>
					<td> </td>
					<td><span><i></i> 00:11:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Practice: Expected value</td>
					<td> </td>
					<td><span><i></i> 00:01:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Solution: Expected value</td>
					<td> </td>
					<td><span><i></i> 00:03:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Law of Large Numbers</td>
					<td> </td>
					<td><span><i></i> 00:08:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Central Limit Theorem - Theory</td>
					<td> </td>
					<td><span><i></i> 00:10:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Central Limit Theorem - Intuition</td>
					<td> </td>
					<td><span><i></i> 00:08:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Central Limit Theorem - Challenge</td>
					<td> </td>
					<td><span><i></i> 00:11:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Central Limit Theorem - Exercise</td>
					<td> </td>
					<td><span><i></i> 00:02:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Central Limit Theorem - Solution</td>
					<td> </td>
					<td><span><i></i> 00:14:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Binomial distribution</td>
					<td> </td>
					<td><span><i></i> 00:16:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Poisson distribution</td>
					<td> </td>
					<td><span><i></i> 00:17:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Real life problems</td>
					<td> </td>
					<td><span><i></i> 00:15:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Section 05: Hypothesis testing</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Intro</td>
					<td> </td>
					<td><span><i></i> 00:01:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>What is a hypothesis?</td>
					<td> </td>
					<td><span><i></i> 00:19:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Significance level and p-value</td>
					<td> </td>
					<td><span><i></i> 00:06:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Type I and Type II errors</td>
					<td> </td>
					<td><span><i></i> 00:05:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Confidence intervals and margin of error</td>
					<td> </td>
					<td><span><i></i> 00:15:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Excursion: Calculating sample size &amp; power</td>
					<td> </td>
					<td><span><i></i> 00:11:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Performing the hypothesis test</td>
					<td> </td>
					<td><span><i></i> 00:20:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Practice: Hypothesis test</td>
					<td> </td>
					<td><span><i></i> 00:01:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Solution: Hypothesis test</td>
					<td> </td>
					<td><span><i></i> 00:06:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>T-test and t-distribution</td>
					<td> </td>
					<td><span><i></i> 00:13:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Proportion testing</td>
					<td> </td>
					<td><span><i></i> 00:10:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Important p-z pairs</td>
					<td> </td>
					<td><span><i></i> 00:08:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Section 06: Regressions</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Intro</td>
					<td> </td>
					<td><span><i></i> 00:02:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Linear Regression</td>
					<td> </td>
					<td><span><i></i> 00:11:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Correlation coefficient</td>
					<td> </td>
					<td><span><i></i> 00:10:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Practice: Correlation</td>
					<td> </td>
					<td><span><i></i> 00:02:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Solution: Correlation</td>
					<td> </td>
					<td><span><i></i> 00:08:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Practice: Linear Regression</td>
					<td> </td>
					<td><span><i></i> 00:01:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Solution: Linear Regression</td>
					<td> </td>
					<td><span><i></i> 00:07:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Residual, MSE &amp; MAE</td>
					<td> </td>
					<td><span><i></i> 00:08:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Practice: MSE &amp; MAE</td>
					<td> </td>
					<td><span><i></i> 00:01:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Solution: MSE &amp; MAE</td>
					<td> </td>
					<td><span><i></i> 00:03:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Coefficient of determination</td>
					<td> </td>
					<td><span><i></i> 00:12:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Root Mean Square Error</td>
					<td> </td>
					<td><span><i></i> 00:06:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Practice: RMSE</td>
					<td> </td>
					<td><span><i></i> 00:01:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Solution: RMSE</td>
					<td> </td>
					<td><span><i></i> 00:02:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Section 07: Advanced regression &amp; machine learning algorithms</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Multiple Linear Regression</td>
					<td> </td>
					<td><span><i></i> 00:16:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Overfitting</td>
					<td> </td>
					<td><span><i></i> 00:05:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Polynomial Regression</td>
					<td> </td>
					<td><span><i></i> 00:13:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Logistic Regression</td>
					<td> </td>
					<td><span><i></i> 00:09:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Decision Trees</td>
					<td> </td>
					<td><span><i></i> 00:21:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Regression Trees</td>
					<td> </td>
					<td><span><i></i> 00:14:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Random Forests</td>
					<td> </td>
					<td><span><i></i> 00:13:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Dealing with missing data</td>
					<td> </td>
					<td><span><i></i> 00:10:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Section 08: ANOVA (Analysis of Variance)</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>ANOVA - Basics &amp; Assumptions</td>
					<td> </td>
					<td><span><i></i> 00:06:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>One-way ANOVA</td>
					<td> </td>
					<td><span><i></i> 00:12:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>F-Distribution</td>
					<td> </td>
					<td><span><i></i> 00:10:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Two-way ANOVA - Sum of Squares</td>
					<td> </td>
					<td><span><i></i> 00:16:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Two-way ANOVA - F-ratio &amp; conclusions</td>
					<td> </td>
					<td><span><i></i> 00:11:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Section 09: Wrap up</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Wrap up</td>
					<td> </td>
					<td><span><i></i> 00:01:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Assignment</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Assignment - Statistics &amp; Probability for Data Science &amp; Machine Learning</td>
					<td> </td>
					<td><span><i></i> 00:00:00</span></td>
				</tr>
								<tr>
					<td colspan="4"> Order your QLS Endorsed Certificate </td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Order your QLS Endorsed Certificate</td>
					<td> </td>
					<td><span><i></i> 00:00:00</span></td>
				</tr>
				</tbody></table></div>

			</div>

Studyhub UK

Data Science

Diploma in Management Studies (DMS)

Diploma in Professional Studies (DPS)

ICDL (International Certification of Digital Literacy)

Advanced Diploma in Statistics & Probability for Data Science & Machine Learning at QLS Level 7

<strong>Gain proficiency in the mastery of Geographic Information Systems (GIS) via ArcGIS Desktop</strong>
        <p>This course teaches you the most important aspects of spatial data analysis using ArcGIS. It is highly beneficial for both those wanting to learn spatial data analysis and/or gain familiarity with the ArcGIS ecosystem

First, we'll start some basic GIS tasks like 'Zooming'. Then, we'll move into more complex processing tasks like 'Geo-Statistics'. We'll also deal with some theoretical concepts related to Spatial Data Analysis, and then we'll focus on implementing some of the most common GIS techniques (all the way showing you how to execute these tasks in ArcGIS Desktop).

The stuff you'll learn from this course will be extremely useful in terms of you being able to implement it on future Spatial Data projects you'll be working on. The course is a hands-on training with real data. It's a step by step course covering both the theory and application of Spatial Data Analysis. This is one of the most comprehensive courses on this topic.  

All the code and supporting files for this course are available at -
https://github.com/PacktPublishing/ArcGIS-Desktop-For-Spatial-Analysis-Go-From-Basic-To-Pro</p>
        <h2>What You Will Learn</h2><p>You will have a thorough knowledge of the ArcGIS Interface and Functionality<br>You will learn about the different toolboxes in ArcGIS and what they can do<br>You can carry out practical spatial data analysis tasks, geoprocessing and mapping using ArcGIS Desktop<br>You learn about advanced topics such as geostatistics and carry them out on actual data<br>You visualize and map spatial data</p>
        <h2>Audience</h2><p>The target audience is the people looking to get started in the field of GIS Analysis use ArcGIS Desktop in academic or professional settings and students should have access to ArcGIS Desktop. You should have prior knowledge of basic spatial data related concepts such as the different data types and coordinate systems.</p>
        <h2>Approach</h2><p>The approach is full of hands-on instructions via video-lectures, interesting and illustrative examples, clear explanations. Each video lecture will teach you a new concept that you can apply to your own data.</p>
        <h2>Key Features</h2><p>The course will teach you to implement some of the most important spatial data analysis techniques in ArcGIS Desktop * You learn to work with real spatial data * Carry our practical map making to display the results of spatial analysis * Learn about advanced topics such as geostatistics and carry them out on actual data</p>
        <h2>Github Repo</h2><p>https://github.com/packtpublishing/arcgis-desktop-for-spatial-analysis-go-from-basic-to-pro</p>
        <h2>About the Author</h2><h3>Minerva Singh</h3><p>Minerva Singh is a PhD graduate from Cambridge University where she specialized in Tropical Ecology. She is also a part-time Data Scientist. As part of her research, she must carry out extensive data analysis, including spatial data analysis. For this purpose, she prefers to use a combination of freeware tools: R, QGIS, and Python. She does most of her spatial data analysis work using R and QGIS. Apart from being free, these are very powerful tools for data visualization, processing, and analysis. She also holds an MPhil degree in Geography and Environment from Oxford University. She has honed her statistical and data analysis skills through several MOOCs, including The Analytics Edge and Statistical. In addition to spatial data analysis, she is also proficient in statistical analysis, machine learning, and data mining.</p>
        <h2>Course Outline</h2><h4>1. Welcome to Spatial Data Analysis and Visualization</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. What is this Course About and Meet the Instructor</p><p style='margin: 0'>Welcome to Spatial Data Analysis and Visualization: What is this Course About and Meet the Instructor</p></td></tr><tr><td style='padding: 15px;'><p>2. Some Spatial Data Analysis Related Concepts</p><p style='margin: 0'>Welcome to Spatial Data Analysis and Visualization: Some Spatial Data Analysis Related Concepts</p></td></tr><tr><td style='padding: 15px;'><p>3. Conclusion to Section 1</p><p style='margin: 0'>Welcome to Spatial Data Analysis and Visualization: Conclusion to Section 1</p></td></tr></tbody></table><br><h4>2. Introduction to ArcGIS Desktop and its Functionality</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. What is ArcGIS Desktop?</p><p style='margin: 0'>Introduction to ArcGIS Desktop and its Functionality: What is ArcGIS Desktop?</p></td></tr><tr><td style='padding: 15px;'><p>2. Accessing and Displaying Spatial Data in ArcGIS</p><p style='margin: 0'>Introduction to ArcGIS Desktop and its Functionality: Accessing and Displaying Spatial Data in ArcGIS</p></td></tr><tr><td style='padding: 15px;'><p>3. Finding and identifying Features and Values in ArcGIS Desktop</p><p style='margin: 0'>Introduction to ArcGIS Desktop and its Functionality: Finding and identifying Features and Values in ArcGIS Desktop</p></td></tr><tr><td style='padding: 15px;'><p>4. Making Selections in ArcGIS</p><p style='margin: 0'>Introduction to ArcGIS Desktop and its Functionality: Making Selections in ArcGIS</p></td></tr><tr><td style='padding: 15px;'><p>5. Zooming and Measuring</p><p style='margin: 0'>Introduction to ArcGIS Desktop and its Functionality: Zooming and Measuring</p></td></tr><tr><td style='padding: 15px;'><p>6. Calculate Shapefile Geometry in ArcGIS</p><p style='margin: 0'>Introduction to ArcGIS Desktop and its Functionality: Calculate Shapefile Geometry in ArcGIS</p></td></tr><tr><td style='padding: 15px;'><p>7. Working With Different Coordinate Systems in ArcGIS</p><p style='margin: 0'>Introduction to ArcGIS Desktop and its Functionality: Working With Different Coordinate Systems in ArcGIS</p></td></tr><tr><td style='padding: 15px;'><p>8. Conclusion to Section 2</p><p style='margin: 0'>Introduction to ArcGIS Desktop and its Functionality: Conclusion to Section 2</p></td></tr></tbody></table><br><h4>3. Working with Raster Data in ArcGIS Desktop</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Displaying Raster Data in ArcGIS</p><p style='margin: 0'>Working with Raster Data in ArcGIS Desktop: Displaying Raster Data in ArcGIS</p></td></tr><tr><td style='padding: 15px;'><p>2. Merge Rasters in ArcGIS</p><p style='margin: 0'>Working with Raster Data in ArcGIS Desktop: Merge Rasters in ArcGIS</p></td></tr><tr><td style='padding: 15px;'><p>3. Band Arithmetic in ArcGIS Desktop</p><p style='margin: 0'>Working with Raster Data in ArcGIS Desktop: Band Arithmetic in ArcGIS Desktop</p></td></tr><tr><td style='padding: 15px;'><p>4. Reclassify a Raster in ArcGIS Desktop</p><p style='margin: 0'>Working with Raster Data in ArcGIS Desktop: Reclassify a Raster in ArcGIS Desktop</p></td></tr><tr><td style='padding: 15px;'><p>5. Resample a Raster in ArcGIS</p><p style='margin: 0'>Working with Raster Data in ArcGIS Desktop: Resample a Raster in ArcGIS</p></td></tr><tr><td style='padding: 15px;'><p>6. Topographic Data Products-Brief Theoretical Introduction</p><p style='margin: 0'>Working with Raster Data in ArcGIS Desktop: Topographic Data Products-Brief Theoretical Introduction</p></td></tr><tr><td style='padding: 15px;'><p>7. Topographic Calculations in ArcGIS Desktop</p><p style='margin: 0'>Working with Raster Data in ArcGIS Desktop: Topographic Calculations in ArcGIS Desktop</p></td></tr><tr><td style='padding: 15px;'><p>8. Clip a Raster to the Extent of a Polygon in ArcGIS Desktop</p><p style='margin: 0'>Working with Raster Data in ArcGIS Desktop: Clip a Raster to the Extent of a Polygon in ArcGIS Desktop</p></td></tr><tr><td style='padding: 15px;'><p>9. Zonal Statistics</p><p style='margin: 0'>Working with Raster Data in ArcGIS Desktop: Zonal Statistics</p></td></tr><tr><td style='padding: 15px;'><p>10. Extract Raster Values to Points</p><p style='margin: 0'>Working with Raster Data in ArcGIS Desktop: Extract Raster Values to Points</p></td></tr><tr><td style='padding: 15px;'><p>11. Geo-referencing a Raster in ArcGIS Desktop</p><p style='margin: 0'>Working with Raster Data in ArcGIS Desktop: Geo-referencing a Raster in ArcGIS Desktop</p></td></tr><tr><td style='padding: 15px;'><p>12. Conclusion to Section 3</p><p style='margin: 0'>Working with Raster Data in ArcGIS Desktop: Conclusion to Section 3</p></td></tr></tbody></table><br><h4>4. Working with Vector Data in ArcGIS Desktop</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Exploratory Data Analysis with Shapefile Attributes in ArcGIS Desktop</p><p style='margin: 0'>Working with Vector Data in ArcGIS Desktop: Exploratory Data Analysis with Shapefile Attributes in ArcGIS Desktop</p></td></tr><tr><td style='padding: 15px;'><p>2. Basic Graphing of Shapefile Attributes in ArcGIS Desktop</p><p style='margin: 0'>Working with Vector Data in ArcGIS Desktop: Basic Graphing of Shapefile Attributes in ArcGIS Desktop</p></td></tr><tr><td style='padding: 15px;'><p>3. Spatial Join with Tabular Data</p><p style='margin: 0'>Working with Vector Data in ArcGIS Desktop: Spatial Join with Tabular Data</p></td></tr><tr><td style='padding: 15px;'><p>4. Spatial Joins in ArcGIS Based on Spatial Location</p><p style='margin: 0'>Working with Vector Data in ArcGIS Desktop: Spatial Joins in ArcGIS Based on Spatial Location</p></td></tr><tr><td style='padding: 15px;'><p>5. Create Choropleth Maps</p><p style='margin: 0'>Working with Vector Data in ArcGIS Desktop: Create Choropleth Maps</p></td></tr><tr><td style='padding: 15px;'><p>6. Split Shapefiles Using ArcGIS</p><p style='margin: 0'>Working with Vector Data in ArcGIS Desktop: Split Shapefiles Using ArcGIS</p></td></tr><tr><td style='padding: 15px;'><p>7. Clip Shapefile in ArcGIS</p><p style='margin: 0'>Working with Vector Data in ArcGIS Desktop: Clip Shapefile in ArcGIS</p></td></tr><tr><td style='padding: 15px;'><p>8. Intersection of Shapefiles in ArcGIS</p><p style='margin: 0'>Working with Vector Data in ArcGIS Desktop: Intersection of Shapefiles in ArcGIS</p></td></tr><tr><td style='padding: 15px;'><p>9. Add Buffer Areas to Shapefiles in ArcGIS Desktop</p><p style='margin: 0'>Working with Vector Data in ArcGIS Desktop: Add Buffer Areas to Shapefiles in ArcGIS Desktop</p></td></tr><tr><td style='padding: 15px;'><p>10. Merge and Append Shapefiles in ArcGIS Desktop</p><p style='margin: 0'>Working with Vector Data in ArcGIS Desktop: Merge and Append Shapefiles in ArcGIS Desktop</p></td></tr><tr><td style='padding: 15px;'><p>11. Dissolve Shapefiles in ArcGIS</p><p style='margin: 0'>Working with Vector Data in ArcGIS Desktop: Dissolve Shapefiles in ArcGIS</p></td></tr><tr><td style='padding: 15px;'><p>12. Conclusion to Section 4</p><p style='margin: 0'>Working with Vector Data in ArcGIS Desktop: Conclusion to Section 4</p></td></tr></tbody></table><br><h4>5. More Advanced Geoprocessing Tasks in ArcGIS: Intro to Basic Geostatistics</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Euclidean Distance Raster Generation in ArcGIS Desktop</p><p style='margin: 0'>More Advanced Geoprocessing Tasks in ArcGIS: Intro to Basic Geostatistics: Euclidean Distance Raster Generation in ArcGIS Desktop</p></td></tr><tr><td style='padding: 15px;'><p>2. Density Analysis in ArcGIS Desktop</p><p style='margin: 0'>More Advanced Geoprocessing Tasks in ArcGIS: Intro to Basic Geostatistics: Density Analysis in ArcGIS Desktop</p></td></tr><tr><td style='padding: 15px;'><p>3. Compute Line Density in ArcGIS</p><p style='margin: 0'>More Advanced Geoprocessing Tasks in ArcGIS: Intro to Basic Geostatistics: Compute Line Density in ArcGIS</p></td></tr><tr><td style='padding: 15px;'><p>4. Compute Point Density in ArcGIS</p><p style='margin: 0'>More Advanced Geoprocessing Tasks in ArcGIS: Intro to Basic Geostatistics: Compute Point Density in ArcGIS</p></td></tr><tr><td style='padding: 15px;'><p>5. Kernel Density for Linear and Point Features in ArcGIS</p><p style='margin: 0'>More Advanced Geoprocessing Tasks in ArcGIS: Intro to Basic Geostatistics: Kernel Density for Linear and Point Features in ArcGIS</p></td></tr><tr><td style='padding: 15px;'><p>6. Interpolation of Point Data-Theory</p><p style='margin: 0'>More Advanced Geoprocessing Tasks in ArcGIS: Intro to Basic Geostatistics: Interpolation of Point Data-Theory</p></td></tr><tr><td style='padding: 15px;'><p>7. Interpolation of Point Data-Application</p><p style='margin: 0'>More Advanced Geoprocessing Tasks in ArcGIS: Intro to Basic Geostatistics: Interpolation of Point Data-Application</p></td></tr><tr><td style='padding: 15px;'><p>8. Mapping Spatial Clusters in ArcGIS Desktop-Theory</p><p style='margin: 0'>More Advanced Geoprocessing Tasks in ArcGIS: Intro to Basic Geostatistics: Mapping Spatial Clusters in ArcGIS Desktop-Theory</p></td></tr><tr><td style='padding: 15px;'><p>9. Mapping Spatial Clusters in ArcGIS Desktop-Application</p><p style='margin: 0'>More Advanced Geoprocessing Tasks in ArcGIS: Intro to Basic Geostatistics: Mapping Spatial Clusters in ArcGIS Desktop-Application</p></td></tr><tr><td style='padding: 15px;'><p>10. Geographically Weighted Regression in ArcGIS-Theory</p><p style='margin: 0'>More Advanced Geoprocessing Tasks in ArcGIS: Intro to Basic Geostatistics: Geographically Weighted Regression in ArcGIS-Theory</p></td></tr><tr><td style='padding: 15px;'><p>11. Geographically Weighted Regression in ArcGIS-Application</p><p style='margin: 0'>More Advanced Geoprocessing Tasks in ArcGIS: Intro to Basic Geostatistics: Geographically Weighted Regression in ArcGIS-Application</p></td></tr><tr><td style='padding: 15px;'><p>12. Model Builder for Automating Geoprocessing</p><p style='margin: 0'>More Advanced Geoprocessing Tasks in ArcGIS: Intro to Basic Geostatistics: Model Builder for Automating Geoprocessing</p></td></tr><tr><td style='padding: 15px;'><p>13. Conclusion to Section 5</p><p style='margin: 0'>More Advanced Geoprocessing Tasks in ArcGIS: Intro to Basic Geostatistics: Conclusion to Section 5</p></td></tr></tbody></table><br><h4>6. Make Simple Maps in ArcGIS</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Examples of ArcGIS Maps</p><p style='margin: 0'>Make Simple Maps in ArcGIS: Examples of ArcGIS Maps</p></td></tr><tr><td style='padding: 15px;'><p>2. Presenting Spatial Data As a Layer File</p><p style='margin: 0'>Make Simple Maps in ArcGIS: Presenting Spatial Data As a Layer File</p></td></tr><tr><td style='padding: 15px;'><p>3. Using Base Maps provided by ArcGIS to Provide Context to Our Map</p><p style='margin: 0'>Make Simple Maps in ArcGIS: Using Base Maps provided by ArcGIS to Provide Context to Our Map</p></td></tr><tr><td style='padding: 15px;'><p>4. Putting Together a Map</p><p style='margin: 0'>Make Simple Maps in ArcGIS: Putting Together a Map</p></td></tr><tr><td style='padding: 15px;'><p>5. Conclusion to Section 6</p><p style='margin: 0'>Make Simple Maps in ArcGIS: Conclusion to Section 6</p></td></tr></tbody></table>

Programming

Gain proficiency in the mastery of Geographic Information Systems (GIS) via ArcGIS Desktop

ArcGIS Desktop for Spatial Analysis: Go from Basic to Pro

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			<h2>Overview
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					<p><span>There is no experience or previous qualifications required for enrolment on this </span><b><span>CompTIA PenTest+ (Ethical Hacking)</span></b>. It is available to all students, of all academic backgrounds.</p>					</div>
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			<h2>Career Path</h2>		</div>
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					<p>Learning this new skill will help you to advance in your career. It will diversify your job options and help you develop new techniques to keep up with the fast-changing world. This skillset will help you to-</p><ul><li>Open doors of opportunities</li><li>Increase your adaptability</li><li>Keep you relevant</li><li>Boost confidence</li></ul><p>And much more!</p>					</div>
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					</div> <h3>Course Curriculum</h3><div><p>6 sections • 67 lectures • 10:48:00 total length</p></div><div><div><div><div><div><div><div><p>•Introduction: 00:09:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Planning a Pen Test: 00:09:00</p></div><div><div><p>•Rules of Engagement: 00:11:00</p></div><div><div><p>•Resources and Budget: 00:07:00</p></div><div><div><p>•Impact and Constraints: 00:05:00</p></div><div><div><p>•Support Resources: 00:13:00</p></div><div><div><p>•Legal Groundwork: 00:12:00</p></div><div><div><p>•Scope Considerations: 00:11:00</p></div><div><div><p>•Lab Environment Setup: 00:23:00</p></div><div><div><p>•Project Strategy and Risk: 00:09:00</p></div><div><div><p>•Scope Vulnerabilities: 00:14:00</p></div><div><div><p>•Compliance-Based Assessments: 00:05:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Scanning and Enumeration: 00:05:00</p></div><div><div><p>•Scanning Demo: 00:11:00</p></div><div><div><p>•Packet Investigation: 00:08:00</p></div><div><div><p>•Packet Inspection Demo: 00:06:00</p></div><div><div><p>•Application and Open-Source Resources: 00:12:00</p></div><div><div><p>•Vulnerability Scanning: 00:09:00</p></div><div><div><p>•Vulnerability Scanning Demo: 00:17:00</p></div><div><div><p>•Target Considerations: 00:16:00</p></div><div><div><p>•Nmap Timing and Performance Options: 00:07:00</p></div><div><div><p>•Prioritization of Vulnerabilities: 00:09:00</p></div><div><div><p>•Common Attack Techniques: 00:12:00</p></div><div><div><p>•Credential Attacks: 00:15:00</p></div><div><div><p>•Weaknesses in Specialized Systems: 00:18:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Remote Social Engineering: 00:07:00</p></div><div><div><p>•Spear Phishing Demo: 00:10:00</p></div><div><div><p>•In-Person Social Engineering: 00:12:00</p></div><div><div><p>•Network-Based Exploits: 00:07:00</p></div><div><div><p>•FTP Exploit Demo: 00:08:00</p></div><div><div><p>•Man-in-the-middle Exploits: 00:07:00</p></div><div><div><p>•Wireless Exploits: 00:14:00</p></div><div><div><p>•Application Exploits, Part 1: 00:06:00</p></div><div><div><p>•SQL Injection Demo: 00:09:00</p></div><div><div><p>•Application Exploits, Part 2: 00:08:00</p></div><div><div><p>•Application Exploits, Part 3: 00:09:00</p></div><div><div><p>•Cross-Site Scripting Demo: 00:07:00</p></div><div><div><p>•Code Vulnerabilities: 00:17:00</p></div><div><div><p>•Local Host Vulnerabilities: 00:05:00</p></div><div><div><p>•Privilege Escalation (Linux): 00:10:00</p></div><div><div><p>•Privilege Escalation (Windows): 00:06:00</p></div><div><div><p>•Misc. Privilege Escalation: 00:08:00</p></div><div><div><p>•Misc. Local Host Vulnerabilities: 00:08:00</p></div><div><div><p>•Physical Security: 00:11:00</p></div><div><div><p>•Post-Exploitation Techniques: 00:11:00</p></div><div><div><p>•Persistence and Stealth: 00:11:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Nmap Scoping &amp; Output Options: 00:21:00</p></div><div><div><p>•Pen Testing Toolbox: 00:07:00</p></div><div><div><p>•Using Kali Linux: 00:06:00</p></div><div><div><p>•Scanners &amp; Credential Tools: 00:10:00</p></div><div><div><p>•Code-Cracking Tools: 00:05:00</p></div><div><div><p>•Open-Source Research Tools: 00:07:00</p></div><div><div><p>•Wireless and Web Pen Testing Tools: 00:11:00</p></div><div><div><p>•Remote Access Tools: 00:06:00</p></div><div><div><p>•Analyzers and Mobile Pen Testing Tools: 00:03:00</p></div><div><div><p>•Other Pen Testing Tools: 00:05:00</p></div><div><div><p>•Using Scripting in Pen Testing: 00:13:00</p></div><div><div><p>•Bash Scripting Basics: 00:15:00</p></div><div><div><p>•Bash Scripting Techniques: 00:10:00</p></div><div><div><p>•PowerShell Scripts: 00:04:00</p></div><div><div><p>•Ruby Scripts: 00:07:00</p></div><div><div><p>•Python Scripts: 00:06:00</p></div><div><div><p>•Scripting Languages Comparison: 00:11:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Writing Reports: 00:16:00</p></div><div><div><p>•Post-Report Activities: 00:06:00</p></div><div><div><p>•Mitigation Strategies: 00:05:00</p></div><div><div><p>•Communication: 00:10:00</p></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div>

Apex Learning

CompTIA Network+

IT Certifications

Certified Ethical Hacker (CEH)

CompTIA A+

CompTIA Security+

Ethical Hacking

CompTIA PenTest+ (Ethical Hacking)

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			<h2>Overview
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					<p><span>This comprehensive course on Recruitment: IT Basics for IT Recruiters</span><b> </b><span>will deepen your understanding on this topic.</span></p><p><span>After successful completion of this course you can acquire the required skills in this sector. This Recruitment: IT Basics for IT Recruiters</span><span> comes with accredited certification from CPD, which will enhance your CV and make you worthy in the job market.   </span></p><p><span>So enrol in this course today to fast-track your career ladder.</span></p>					</div>
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			<h2>How will I get my certificate?</h2>		</div>
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					<p><span>You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate.</span></p>					</div>
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			<h2>Who is This course for?</h2>		</div>
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					<p><span>There is no experience or previous qualifications required for enrolment on this Recruitment: IT Basics for IT Recruiters</span><span>. It is available to all students, of all academic backgrounds.</span></p>					</div>
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			<h2>Requirements</h2>		</div>
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					<p><span>Our Recruitment: IT Basics for IT Recruiters</span><span> is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G.</span></p>					</div>
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			<h2>Career Path</h2>		</div>
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					<p><span>Learning this new skill will help you to advance in your career. It will diversify your job options and help you develop new techniques to keep up with the fast-changing world. This skillset will help you to-</span></p><ul><li><span>Open doors of opportunities</span></li><li><span>Increase your adaptability</span></li><li><span>Keep you relevant</span></li><li><span>Boost confidence</span></li></ul><p><span>And much more!</span></p>					</div>
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					</div> <h3>Course Curriculum</h3><div><p>9 sections • 62 lectures • 05:10:00 total length</p></div><div><div><div><div><div><div><div><p>•Introduction: 00:02:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Server: 00:08:00</p></div><div><div><p>•What is hardware and software?: 00:04:00</p></div><div><div><p>•Project Life Cycle: 00:06:00</p></div><div><div><p>•Software Development Life Cycle: 00:08:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Methodologies: Scrum, Agile, Kanban, Waterfall, Lean: 00:09:00</p></div><div><div><p>•CMS: 00:04:00</p></div><div><div><p>•API: 00:04:00</p></div><div><div><p>•Stacks: 00:03:00</p></div><div><div><p>•Native &amp; Hybrid Native Apps: 00:02:00</p></div><div><div><p>•CI / CD / Deployment tools: 00:04:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•CTO: 00:13:00</p></div><div><div><p>•IT Architects: 00:08:00</p></div><div><div><p>•Product Owner: 00:12:00</p></div><div><div><p>•Product Manager: 00:06:00</p></div><div><div><p>•PO vs Product Manager: 00:04:00</p></div><div><div><p>•Project Manager: 00:13:00</p></div><div><div><p>•Product Owner vs Project Manager vs Product Manager: 00:07:00</p></div><div><div><p>•Business Analysts: 00:09:00</p></div><div><div><p>•Business Intelligence Analyst: 00:06:00</p></div><div><div><p>•Data Engineer: 00:05:00</p></div><div><div><p>•Data Scientist: 00:07:00</p></div><div><div><p>•Data Engineer vs Data Scientist: 00:07:00</p></div><div><div><p>•Agile Coach: 00:14:00</p></div><div><div><p>•Scrum Master: 00:08:00</p></div><div><div><p>•Agile Coach vs Scrum Master: 00:01:00</p></div><div><div><p>•Frontend Developer: 00:06:00</p></div><div><div><p>•Backend Developer: 00:06:00</p></div><div><div><p>•Fullstack Developer: 00:04:00</p></div><div><div><p>•Developers: Frontend, Backend and Fullstack: 00:02:00</p></div><div><div><p>•iOS Developer: 00:03:00</p></div><div><div><p>•Android Developer: 00:04:00</p></div><div><div><p>•UX Designers: 00:09:00</p></div><div><div><p>•UI Design: 00:08:00</p></div><div><div><p>•UX vs UI Design: what is the difference?: 00:04:00</p></div><div><div><p>•QA Engineers and Testers: 00:09:00</p></div><div><div><p>•System Administrators: 00:07:00</p></div><div><div><p>•DevOps: 00:05:00</p></div><div><div><p>•SEO Specialists: who are they?: 00:10:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Programming Languages and Frameworks. Introduction: 00:01:00</p></div><div><div><p>•Programming languages and frameworks: 00:08:00</p></div><div><div><p>•JavaScript: 00:02:00</p></div><div><div><p>•Java: 00:03:00</p></div><div><div><p>•Python: 00:01:00</p></div><div><div><p>•C: 00:02:00</p></div><div><div><p>•C#: 00:02:00</p></div><div><div><p>•C++: 00:03:00</p></div><div><div><p>•SWIFT: 00:02:00</p></div><div><div><p>•Objective C: 00:01:00</p></div><div><div><p>•HTML: 00:02:00</p></div><div><div><p>•PHP: 00:02:00</p></div><div><div><p>•Ruby: 00:02:00</p></div><div><div><p>•SQL: 00:02:00</p></div><div><div><p>•Go: 00:01:00</p></div><div><div><p>•R: 00:01:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Database: 00:05:00</p></div><div><div><p>•Types of Databases: 00:07:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•The day of an IT Recruiter: 00:05:00</p></div><div><div><p>•Key principles: 00:03:00</p></div><div><div><p>•Sourcing Tips: 00:03:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Thank you for taking part in this course!: 00:01:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Assignment - Recruitment: IT Basics for IT Recruiters: 00:00:00</p></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div>

Online Course Marketing

Recruitment Consultant

IT Skills

Computer Skills

Trainers Course

Recruitment: IT Basics for IT Recruiters

<div id="course-pills-1">Duration<p>3 Days</p><p>18 CPD hours</p>This course is intended for<p>Server administrators<br />Network engineers<br />Systems engineers<br />Consulting systems engineers<br />Technical solutions architects<br />Network administrators<br />Storage administrators<br />Network managers<br />Cisco integrators and partners</p>Overview<p>After taking this course, you should be able to:<br />Describe and implement Fibre Channel, zoning, and N-Port Virtualization (NPV) features on Cisco UCS<br />Describe and implement Fibre Channel over Ethernet (FCoE) on Cisco UCS<br />Describe Cisco UCS policies for service profiles<br />Describe Cisco Adapter Fabric Extender (FEX) and Single Root I/O Virtualization<br />Describe and implement Role-Based Access Control (RBAC) on Cisco UCS<br />Describe and implement external authentication providers on Cisco UCS Manager<br />Describe and implement key management on Cisco UCS Manager<br />Describe Cisco UCS Director<br />Describe and implement Cisco Intersight<br />Describe the scripting options for Cisco UCS Manager<br />Describe and implement monitoring on Cisco UCS Manager</p><p>The Configuring Cisco Unified Computing System (DCCUCS) v1.0 shows you how to deploy, secure, operate, and maintain Cisco Unified Computing System? (Cisco UCSÂ©) B-series blade servers, Cisco UCS C-Series, and S-Series rack servers for use in data centers. You will learn how to implement management and orchestration software for Cisco UCS. You will gain hands-on practice: configuring key features of Cisco UCS, Cisco UCS Director, and Cisco UCS Manager; implementing UCS management software including Cisco UCS Manager and Cisco Intersight?; and more.</p></div><div id="course-pills-2"><h4>Implementing Cisco UCS Storage Area Network (SAN)</h4><ul><li>SAN Introduction</li><li>Cisco UCS Fabric Interconnect Fibre Channels modes</li><li>Named VSANs</li><li>Cisco UCS Fibre Channel and FCoE Storage Connectivity</li></ul><h4>Describing Cisco UCS Policies for Service Profiles</h4><ul><li>Storage Policies and Profiles</li><li>Basic Input Output System (BIOS) Policies</li><li>Boot Policy</li><li>Intelligent Platform Management Interface (IPMI) Policies</li><li>Scrub Policies</li><li>Maintenance Policies</li></ul><h4>Describing Cisco Adapter FEX and Single Root I/O Virtualization</h4><ul><li>Cisco FEX Overview</li><li>Cisco Adapter FEX</li><li>Single Root I/O Virtualization</li></ul><h4>Implementing RBAC on Cisco UCS</h4><ul><li>RBAC in Cisco UCS</li><li>Users, Roles, and Privileges</li><li>Functions of Organizations and Locales</li><li>Effective Rights of a User</li></ul><h4>Implementing External Authentication Providers</h4><ul><li>Options for External Authentication Providers</li></ul><h4>Implementing Key Management on Cisco UCS Manager</h4><ul><li>Public Key Infrastructure</li></ul><h4>Implementing Cisco UCS Director</h4><ul><li>Cisco UCS Director Overview</li><li>Policies, Virtual Data Centers, and Catalogs</li><li>Cisco UCS Director Virtualization Support</li><li>Managing Compute with Cisco UCS Director</li><li>Cisco UCS Manager Orchestration</li><li>Self-Service Portal</li><li>Reporting and Monitoring in Cisco UCS Director</li></ul><h4>Implementing Cisco Intersight</h4><ul><li>Cisco UCS Director Overview</li><li>Important Features of Cisco Intersight</li></ul><h4>Describing the Scripting Options for Cisco UCS Manager</h4><ul><li>Cisco UCS Manager XML API</li><li>Cisco UCS Management Information Tree</li><li>Managed Object Browser</li><li>Cisco UCS PowerTool</li><li>Cisco UCS Python Software Development Kit (SDK)</li></ul><h4>Implementing Key Management on Cisco UCS Manager</h4><ul><li>Public Key Infrastructure</li></ul><h4>Implementing Cisco Intersight</h4><ul><li>Cisco Intersight Overview</li><li>Important Features of Cisco Intersight</li></ul><h4>Describing the Scripting Options for Cisco UCS Manager</h4><ul><li>Cisco UCS Manager XML API</li><li>Cisco UCS Management Information Tree</li><li>Managed Object Browser</li><li>Cisco UCS Manager PowerTool</li><li>Cisco UCS Python SDK</li></ul><h4>Implementing Monitoring on Cisco UCS Manager</h4><ul><li>Logging Sources in Cisco UCS Manager</li><li>Port Monitoring Capabilities of Cisco UCS Manager</li><li>Simple Network Management Protocol (SNMP) Security Ramifications</li><li>Cisco UCS Manager Call Home Feature</li></ul><h4>Lab outline</h4><ul><li>Configure Pod-Specific Device Aliases</li><li>Configure Zoning</li><li>Configure VSANs in Cisco UCS Manager</li><li>Configure Unified Ports on Cisco UCS Fabric Interconnects</li><li>Install and Boot VMware Elastic Sky X Integrated (ESXi) on Cisco UCS from the FCoE Logical Unit Number (LUN) via FCoE</li><li>Configure RBAC</li><li>Configure Cisco UCS Manager to Authenticate Users via Open Lightweight Directory Access Protocol (OpenLDAP)</li><li>Configure a Trusted Point and Key Ring in Cisco UCS Manager</li><li>Configure Cisco UCS with Cisco Intersight</li><li>Configure Cisco UCS Manager Using Scripting</li><li>Implement Syslog and Call Home</li></ul></div><div id="course-pills-3"><h4>Additional course details:</h4><br /><p>Nexus Humans Cisco Configuring Cisco Unified Computing System v1.0 (DCCUCS) training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. </p><p></p> This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. <p></p>Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success.  <p></p>While we feel this is the best course for the Cisco Configuring Cisco Unified Computing System v1.0 (DCCUCS) course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you.  <p></p>Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.<p></p></div>

Cisco Certified Network Associate (CCNA)

Cisco Certified Network Professional certification (CCNP)

Certificate in Information Security Management Principles (CISMP)

Cisco Certified Entry Networking Technician (CCENT)

Cisco Certified Internetwork Expert (CCIE)

IT Networking Fundamentals

Cisco Configuring Cisco Unified Computing System v1.0 (DCCUCS)

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	<h3><b>Description: </b></h3>
<p><span>Gaming has been considered as one of the most popular hobbies in the world. Since the demand for games is not decreasing just yet, game development has continued to grow and develop. If you are interested in gaming, you need to put in your mind that learning the basics will help you in this industry. But adding lessons on how to develop and test games could take you a step ahead which this course will be able to provide. You will also be provided with social gaming guide and financial tips that could take you even further in the gaming industry.</span></p>
<h3><b>Who is the course for?</b></h3>
<ul>
<li><span>Game developers or professionals who want to improve their gaming basics for development</span></li>
<li><span>People who have an interest in becoming part of the game development industry.</span></li>
</ul>
<h3><b>Entry Requirement:</b></h3>
<ul>
<li><span>This course is available to all learners, of all academic backgrounds. </span></li>
<li><span>Learners should be aged 16 or over to undertake the qualification.</span></li>
<li><span>Good understanding of English language, numeracy and ICT are required to attend this course.</span></li>
</ul>
<h3><b>Assessment:  </b></h3>
<ul>
<li><span>At the end of the course, you will be required to sit an online multiple-choice test. Your test will be assessed automatically and immediately so that you will instantly know whether you have been successful.</span></li>
<li><span>Before sitting for your final exam, you will have the opportunity to test your proficiency with a mock exam. </span></li>
</ul>
<h3><b>Certification: </b></h3>
<ul>
<li><span>After you have successfully passed the test, you will be able to obtain an Accredited Certificate of Achievement. You can however also obtain a Course Completion Certificate following the course completion without sitting for the test. Certificates can be obtained either in hard copy at the cost of £39 or in PDF format at the cost of £24. </span></li>
<li><span>PDF certificate's turnaround time is 24 hours, and for the hardcopy certificate, it is 3-9 working days.</span></li>
</ul>
<h3><b>Why choose us?</b></h3>
<ul>
<li><span>Affordable, engaging &amp; high-quality e-learning study materials;</span></li>
<li><span>Tutorial videos/materials from the industry leading experts;</span></li>
<li><span>Study in a user-friendly, advanced online learning platform;</span></li>
<li><span>Efficient exam systems for the assessment and instant result; </span></li>
<li><span>The UK &amp; internationally recognized accredited qualification;</span></li>
<li><span>Access to course content on mobile, tablet or desktop from anywhere anytime;</span></li>
<li><span>The benefit of career advancement opportunities;</span></li>
<li><span>24/7 student support via email.</span></li>
</ul>
<h3><b>Career Path:</b></h3>
<p><span>The Gaming 5 Course Bundle would be beneficial for the following careers:</span></p>
<ul>
<li><span>Animator</span></li>
<li><span>Audio Engineer</span></li>
<li><span>Beta Tester</span></li>
<li><span>Creative Director</span></li>
<li><span>Executive Producer</span></li>
<li><span>Game Developer</span></li>
<li><span>Game Programmer</span></li>
<li><span>Game Tester</span></li>
<li><span>Games Artist</span></li>
<li><span>Product Manager</span></li>
<li><span>QA Tester</span></li>
<li><span>Software Developer.</span></li>
</ul>
		</div><table width="100%">				<tbody><tr>
					<td colspan="4">Gaming Basics</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Introduction</td>
					<td> </td>
					<td><span><i></i> 00:30:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Understanding Consoles</td>
					<td> </td>
					<td><span><i></i> 01:00:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Using Your Computer</td>
					<td> </td>
					<td><span><i></i> 01:00:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Using Your Phone</td>
					<td> </td>
					<td><span><i></i> 01:00:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Using the Internet</td>
					<td> </td>
					<td><span><i></i> 00:30:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Where to Find Free Software</td>
					<td> </td>
					<td><span><i></i> 01:00:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Understanding Accessories Dealing with Drugs</td>
					<td> </td>
					<td><span><i></i> 00:30:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Wrapping Up</td>
					<td> </td>
					<td><span><i></i> 00:15:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Developing Games</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Introduction To Game Creation</td>
					<td> </td>
					<td><span><i></i> 00:30:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Essential Tools</td>
					<td> </td>
					<td><span><i></i> 01:00:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>2D Game Creation Software</td>
					<td> </td>
					<td><span><i></i> 01:00:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>3D Game Creation Software</td>
					<td> </td>
					<td><span><i></i> 01:00:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>3D Game Creation</td>
					<td> </td>
					<td><span><i></i> 00:30:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Game Modification</td>
					<td> </td>
					<td><span><i></i> 01:00:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>How To Create  a Game on a Social Site</td>
					<td> </td>
					<td><span><i></i> 00:30:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Wrapping Up</td>
					<td> </td>
					<td><span><i></i> 00:15:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Testing Games</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Introduction to Game Testing</td>
					<td> </td>
					<td><span><i></i> 01:00:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Two Rules of Game Testing</td>
					<td> </td>
					<td><span><i></i> 01:00:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>How to Put a Resume Together</td>
					<td> </td>
					<td><span><i></i> 01:00:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>How give  Examples During Job Interview</td>
					<td> </td>
					<td><span><i></i> 00:30:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Contacting Game Developers</td>
					<td> </td>
					<td><span><i></i> 01:00:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Use the Correct Search Keywords</td>
					<td> </td>
					<td><span><i></i> 00:30:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Wrapping Up</td>
					<td> </td>
					<td><span><i></i> 00:15:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Social Gaming Guide</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Introduction</td>
					<td> </td>
					<td><span><i></i> 01:00:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>How to Use the Application Launcher</td>
					<td> </td>
					<td><span><i></i> 00:30:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Farmville on Facebook</td>
					<td> </td>
					<td><span><i></i> 01:00:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Facebook Words with Friends</td>
					<td> </td>
					<td><span><i></i> 01:00:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Facebook Social City</td>
					<td> </td>
					<td><span><i></i> 01:00:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Finding Free Social Games</td>
					<td> </td>
					<td><span><i></i> 01:00:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Being A Hero In Social Site Game</td>
					<td> </td>
					<td><span><i></i> 00:30:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>The Best Social Site Games</td>
					<td> </td>
					<td><span><i></i> 01:00:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>How to separate learning myths from reality</td>
					<td> </td>
					<td><span><i></i> 00:30:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Financial Tips for Gamer</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Introduction</td>
					<td> </td>
					<td><span><i></i> 01:00:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Basic Concept of Internet Safety</td>
					<td> </td>
					<td><span><i></i> 01:00:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>A Simple Guide for Buying budget Gaming</td>
					<td> </td>
					<td><span><i></i> 01:00:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Keep Track of what you Spend</td>
					<td> </td>
					<td><span><i></i> 00:30:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Why Being Naive Can Make Your Fortune</td>
					<td> </td>
					<td><span><i></i> 00:30:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>If you Need Help Get It</td>
					<td> </td>
					<td><span><i></i> 01:00:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Be Careful not to Get Hooked</td>
					<td> </td>
					<td><span><i></i> 01:00:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>How to Handle Difficult Conversations at Work</td>
					<td> </td>
					<td><span><i></i> 00:30:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>The Best Way to Finance Games</td>
					<td> </td>
					<td><span><i></i> 00:15:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Additional Supporting Materials</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Game QA &amp; Testing</td>
					<td> </td>
					<td><span><i></i> 00:00:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Become A Game Tester</td>
					<td> </td>
					<td><span><i></i> 00:00:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Game Testing Changers</td>
					<td> </td>
					<td><span><i></i> 00:00:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>2D Game</td>
					<td> </td>
					<td><span><i></i> 00:00:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Beginning Game Development with Python and Pygame</td>
					<td> </td>
					<td><span><i></i> 00:00:00</span></td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Game Development XNA GameStudio</td>
					<td> </td>
					<td><span><i></i> 00:00:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Refer A Friend</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Refer A Friend</td>
					<td> </td>
					<td><span><i></i> 00:00:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Mock Exam</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Mock Exam- Gaming 5 Course Bundle</td>
					<td> </td>
					<td><span><i></i> 00:30:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Final Exam</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Final Exam- Gaming 5 Course Bundle</td>
					<td> </td>
					<td><span><i></i> 00:30:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Order Your Certificate and Transcript</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Order Your Certificates and Transcripts</td>
					<td> </td>
					<td><span><i></i> 00:00:00</span></td>
				</tr>
				</tbody></table>

John Academy

Game Design

Gaming

Online Course Creation

Game Development

Video Game

Gaming 5 Course Bundle

<strong>Welcome to this beginner's level course on Microsoft SQL Servers. Understand the concepts of SQL and learn to create a new database and table to perform various operations on it, with live running queries as examples. Work on hands-on exercises and understand database concepts in a real-world scenario.</strong>
        <p>SQL Server is a relational database management system (RDBMS) developed by Microsoft. SQL Server also allows user-defined composite types (UDTs) to be used. The SQL Server services operate within SQL server instances, allowing people to do machine learning and data analytics.

In this course, you will understand the difference between SQL and NoSQL. You will query SQL and learn about built-in SQL functions. You will create and modify databases and tables using the CREATE DATABASE and CREATE TABLE statements. You will create, select, and modify records and create constraints in SQL. You will advance to create indexes, drop tables, and databases in SQL. You will learn about operators (AND, OR, NOT, LIKE, BETWEEN, IN, LIKE), functions, statements, and constraints in SQL. You will look at stored procedures and aliases, and learn to back up databases in SQL. You will use the WHERE clause to query and learn about the SELECT and DISTINCT functions. You will arrange data using the ORDER BY keyword and ASC and DESC keywords.

After completing the course, you will thoroughly understand SQL's features and components. You will create complex databases and maintain existing databases. Finally, you will acquire complex SQL query capabilities and write complex queries.

All resources are available at: https://github.com/PacktPublishing/SQL-Server-Course-for-Beginners-with-100-examples</p>
        <h2>What You Will Learn</h2><p>Create databases and tables from the start<br>Learn to handle MySQL queries<br>Learn to query SQL to manipulate records in tables<br>Explore functions, statements, and constraints in SQL<br>Create and maintain complex databases and table structures<br>Write complex query statements for maximum data optimization</p>
        <h2>Audience</h2><p>This course delivers a substantial learning experience for database creators, web developers, application developers, and programmers who must operate with SQL and database structures. Database analysts and administrators who are looking to advance/refresh their knowledge skillsets can benefit from this course. The course has no additional prerequisites besides basic computer use knowledge.</p>
        <h2>Approach</h2><p>Well-structured and high-quality video lectures provide step-by-step explanations in a tutorial-like environment, making it easily understandable for beginners about a new database, tables, and their features with live running queries as examples. The course also provides carefully created quizzes to refresh and hone your SQL skillsets.</p>
        <h2>Key Features</h2><p>Understand the SQL query process and the role of databases in real-world applications * Create new databases and tables and perform operations to manipulate records using SQL queries * Master SQL querying and write complex query statements to enhance your understanding of MySQL</p>
        <h2>Github Repo</h2><p>https://github.com/PacktPublishing/SQL-Server-Course-for-Beginners-with-100-examples</p>
        <h2>About the Author</h2><h3>Amit Diwan</h3><p>Studyopedia was founded by Amit Diwan in 2018 after working for Tutorialspoint , IIT, IASRI, Sitepoint, DU, and C# Corner. Studyopedia sells courses on Udemy, Tutorialspoint, Geeksforgeeks, and Skillshare, providing video courses to master various technologies and programming languages, databases, frameworks, Python, data science, machine learning, Java, Android, C/C++, HTML5, Bootstrap, JavaScript, jQuery, PHP, CSS, WordPress, Drupal, Joomla, Magento, osCommerce, OpenCart, PrestaShop, and other disciplines. Studyopedia delivers high-quality video courses to millions of students and professionals enrolled through their website on multiple programming languages and technologies.</p>
        <h2>Course Outline</h2><h4>1. SQL Introduction</h4><p>This section focuses on a cursory introduction to SQL, the benefits of using SQL, and also the features of SQL.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Introduction</p><p style='margin: 0'>Learn what SQL is and how it is based on RDBMS. We will discuss the features and Microsoft SQL Server and SQL Server Management Studio.</p></td></tr><tr><td style='padding: 15px;'><p>2. SQL Versus NoSQL</p><p style='margin: 0'>Learn the difference between SQL and NoSQL. We have considered the example of MySQL (SQL-based) and MongoDB (NoSQL-based) to understand the concept.</p></td></tr></tbody></table><br><h4>2. SQL Installation and Setup</h4><p>This section focuses on the installation and setup process of SQL server over Windows 10 and 11 and also to fix installation errors.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Install SQL Server on Windows 10</p><p style='margin: 0'>Learn how to download and install Microsoft SQL Server on Windows 10. We will also install SQL Server Management Studio (SSMS).</p></td></tr><tr><td style='padding: 15px;'><p>2. Install SQL Server on Windows 11</p><p style='margin: 0'>Learn how to download and install Microsoft SQL Server on Windows 11. We will also install SQL Server Management Studio (SSMS).</p></td></tr><tr><td style='padding: 15px;'><p>3. Fix SQL Server Installation Error</p><p style='margin: 0'>While installing SQL Server, you may get the following error: Learn how to fix the following error while installing Microsoft SQL Server 2019: A required file could not be downloaded. This could mean the version of the installer is no longer supported.</p></td></tr></tbody></table><br><h4>3. Create and Insert</h4><p>This section focuses over creating a database and table and adding records or populating the table and database.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Create a Database</p><p style='margin: 0'>Learn how to create a new database in SQL Server. The CREATE DATABASE statement is used to create a new SQL server database.</p></td></tr><tr><td style='padding: 15px;'><p>2. Create a Table</p><p style='margin: 0'>Learn how to create a new table with SQL Server. The CREATE TABLE statement is used to create a new table in SQL Server.</p></td></tr><tr><td style='padding: 15px;'><p>3. Insert Records</p><p style='margin: 0'>Use the INSERT INTO Statement in SQL to learn how to insert records in a table.</p></td></tr></tbody></table><br><h4>4. Select Records in SQL</h4><p>This section delves over records in SQL, how to select them, how to select distinct elements, and use the where clause to segregate records.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. SELECT Statement in SQL</p><p style='margin: 0'>Learn how to select records in SQL using the SELECT statement. We will also see how to choose multiple columns in a single query.</p></td></tr><tr><td style='padding: 15px;'><p>2. SELECT DISTINCT Statement in SQL</p><p style='margin: 0'>Learn how to select and return only distinct values from a table using the SQL SELECT DISTINCT statement.</p></td></tr><tr><td style='padding: 15px;'><p>3. WHERE Clause in SQL</p><p style='margin: 0'>Learn how to work with the WHERE clause in SQL. WHERE clause filters records based on condition(s).</p></td></tr></tbody></table><br><h4>5. Order Records in SQL</h4><p>This section focuses on the order records function of SQL using the ORDER BY keyword.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. ORDER BY Keyword in SQL</p><p style='margin: 0'>Learn how to order records in SQL using the ORDER BY keyword. The default sorts in ascending order. We will see examples of both ASC and DESC keywords as well.</p></td></tr></tbody></table><br><h4>6. Operators in SQL</h4><p>This section focuses on the arithmetic and logical operators used in SQL, including AND, OR, NOT, IN, BETWEEN, and LIKE.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. AND Operator</p><p style='margin: 0'>Learn how to work with the AND operator in SQL to display records only if both conditions are TRUE. These two conditions should be separated by the AND operator.</p></td></tr><tr><td style='padding: 15px;'><p>2. OR Operator</p><p style='margin: 0'>Learn how to work with the OR operator in SQL to display records only if one condition is TRUE. The OR operator should separate these two conditions.</p></td></tr><tr><td style='padding: 15px;'><p>3. NOT Operator</p><p style='margin: 0'>Learn how to work with the NOT operator in SQL to display records only if the condition isn't met, that is, FALSE.</p></td></tr><tr><td style='padding: 15px;'><p>4. IN Operator</p><p style='margin: 0'>Learn how to implement the IN operator in SQL. We will check whether a specific value matches.</p></td></tr><tr><td style='padding: 15px;'><p>5. BETWEEN Operator</p><p style='margin: 0'>Learn how to implement the BETWEEN operator in SQL. We will find values in a range.</p></td></tr><tr><td style='padding: 15px;'><p>6. LIKE Operator</p><p style='margin: 0'>Learn how to implement the LIKE operator in SQL. We will find values based on a specific pattern using percentages and underscore.</p></td></tr></tbody></table><br><h4>7. Built-In Functions in SQL</h4><p>This section focuses on the built-in functions in SQL and helps us understand maximum, minimum, sum, average, and count functions in detail.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. MAX() Function</p><p style='margin: 0'>Learn how to implement the MAX() function in SQL. We will find the maximum of column values.</p></td></tr><tr><td style='padding: 15px;'><p>2. MIN() Function</p><p style='margin: 0'>Learn how to implement the MIN() function in SQL. We will find the minimum of column values.</p></td></tr><tr><td style='padding: 15px;'><p>3. SUM() Function</p><p style='margin: 0'>Learn how to implement the SUM() function in SQL. We will find the sum of column values.</p></td></tr><tr><td style='padding: 15px;'><p>4. AVG() Function</p><p style='margin: 0'>Learn how to implement the AVG() function in SQL. We will find the average of column values.</p></td></tr><tr><td style='padding: 15px;'><p>5. COUNT() Function</p><p style='margin: 0'>Learn how to implement the COUNT() function in SQL. We will find the count of the number of rows.</p></td></tr></tbody></table><br><h4>8. Constraints in SQL</h4><p>This section focuses on constraints in SQL and the different types of constraints that can be used to manipulate data.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. NOT NULL Constraint</p><p style='margin: 0'>Learn how to work with the NOT NULL constraint in SQL to enforce a column with values, that is, not null. Remember, as columns can have NULL by default, we use the NOT NULL constraint to enforce a column NOT to accept values.</p></td></tr><tr><td style='padding: 15px;'><p>2. UNIQUE Constraint</p><p style='margin: 0'>Learn how to work with the UNIQUE constraint in SQL to uniquely identify each record in a database table. It enforces the uniqueness of column values.</p></td></tr><tr><td style='padding: 15px;'><p>3. PRIMARY KEY Constraint</p><p style='margin: 0'>Learn how to work with the PRIMARY KEY constraint in SQL. A PRIMARY KEY uniquely identifies each record. Not a Primary Key column can never have NULL values.</p></td></tr><tr><td style='padding: 15px;'><p>4. FOREIGN KEY Constraint</p><p style='margin: 0'>Learn how to work with the FOREIGN KEY constraint in SQL. A FOREIGN KEY is a field in one table that refers to the PRIMARY KEY in another. A child table is a table with a foreign key.</p></td></tr><tr><td style='padding: 15px;'><p>5. CHECK Constraint</p><p style='margin: 0'>Learn how to work with the CHECK constraint in SQL to allow only specific values for a column. You can limit the value range set in a column, for example, Age > 18, Marks > 75, and so on.</p></td></tr></tbody></table><br><h4>9. Alter and Update in SQL</h4><p>This section focuses on the ALTER TABLE and UPDATE TABLE functions in SQL that allow us to manipulate records in a table.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. ALTER TABLE Statement</p><p style='margin: 0'>Learn how to work with the ALTER TABLE in SQL to add or delete columns in the existing table. To add a column to an existing table, use the ALTER TABLE with ADD command. To delete a column from an existing table, use the ALTER TABLE with DROP COLUMN.</p></td></tr><tr><td style='padding: 15px;'><p>2. UPDATE Statement</p><p style='margin: 0'>Learn how to work with the UPDATE statement in SQL to update existing records in a table. Use the WHERE clause with the UPDATE statement to avoid updating all records in the table.</p></td></tr><tr><td style='padding: 15px;'><p>3. Aliases</p><p style='margin: 0'>Learn how to work with Aliases in SQL to give a temporary name to a table or column. The AS keyword creates an alias, making column names more readable. Remember that the alias's existence expires when that query's duration ends.</p></td></tr></tbody></table><br><h4>10. Advanced SQL</h4><p>This advanced section delves deep into stored procedures, indexes, and other advanced statements. We will also look at backing up a database and removing tables from a database.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Stored Procedures in SQL</p><p style='margin: 0'>Use the CREATE PROCEDURE statement to learn how to work with stored procedures in SQL. If you want to reuse a query again and again, then create a procedure and save the query in it. Call the procedure whenever you need that same query. Therefore, stored procedures work like a function.</p></td></tr><tr><td style='padding: 15px;'><p>2. Indexes in SQL</p><p style='margin: 0'>Learn how to work with the CREATE INDEX statement in SQL to create indexes in a table. Indexes retrieve data quickly from the database. We will also see how to delete indexes using the DROP INDEX statement.</p></td></tr><tr><td style='padding: 15px;'><p>3. SELECT INTO Statement in SQL</p><p style='margin: 0'>Learn how to work with the SELECT INTO statement in SQL to create a backup copy of your table to a new table. The new table will have the same type and columns as in the first.</p></td></tr><tr><td style='padding: 15px;'><p>4. SELECT TOP Clause in SQL</p><p style='margin: 0'>Learn how to implement the SELECT TOP statement in SQL. We will work with the SELECT TOP PERCENT statement as well.</p></td></tr><tr><td style='padding: 15px;'><p>5. Back Up a Database in SQL</p><p style='margin: 0'>Learn how to back up a database in SQL. We will back up the database in a local directory with the extension .bak.</p></td></tr><tr><td style='padding: 15px;'><p>6. SQL Views</p><p style='margin: 0'>Learn how to work with Views in SQL. A view is a virtual table created from the actual table, displaying the current result set. We will use the CREATE VIEW and DROP VIEW statements to develop and delete views.</p></td></tr><tr><td style='padding: 15px;'><p>7. Drop a Table in SQL</p><p style='margin: 0'>Learn how to drop a table in SQL. Dropping will delete all the records of the table. It will also obliterate the existence of the table.</p></td></tr></tbody></table>

Database Programming

SQL Server

MySQL

Welcome to this beginner's level course on Microsoft SQL Servers. Understand the concepts of SQL and learn to create a new database and table to perform various operations on it, with live running queries as examples. Work on hands-on exercises and understand database concepts in a real-world scenario.

SQL Server Course for Beginners with 100+ examples

<strong>Pre-process and Analyze Satellite Remote Sensing Data with Free Software</strong>
        <p>Enroll in my latest course on how to learn all about Basic Satellite Remote Sensing or perhaps you have prior experiences in GIS or tools like R and QGIS? You don't want to spend 100s and 1000s of dollars on buying commercial software for imagery analysis? The next step for you is to gain proficiency in satellite remote sensing data analysis.

This course is hands-on training with real remote sensing data with open source tools! This course provides a foundation to carry out practical, real-life remote sensing analysis tasks in popular and free software frameworks with real spatial data. By taking this course, you are taking an important step forward in your GIS journey to become an expert in geospatial analysis. Why Should You Take My Course? The author is an Oxford University MPhil (Geography and Environment), graduate. She also completed a Ph.D. at Cambridge University (Tropical Ecology and Conservation). She has several years of experience in analyzing real-life spatial remote sensing data from different sources and producing publications for international peer-reviewed journals. 

In this course, actual satellite remote sensing data such as Landsat from USGS and radar data from JAXA will be used to give practical hands-on experience of working with remote sensing and understanding what kind of questions remote sensing can help us answer. This course will ensure you learn and put remote sensing data analysis into practice today and increase your proficiency in geospatial analysis. Remote sensing software tools are very expensive, and their cost can run into thousands of dollars. Instead of shelling out so much money or procuring pirated copies (which puts you at risk of prosecution), you will learn to carry out some of the most important and common remote sensing analysis tasks using a number of popular, open-source GIS tools such as R, QGIS, GRASS, and ESA-SNAP.  All of which are in great demand in the geospatial sector and improving your skills in these is a plus for you. You will also learn about the different sources of remote sensing data there are and how to obtain these free of charge and process them using free software.

All the code and supporting files for this course are available at -
https://github.com/PacktPublishing/Satellite-Remote-Sensing-Data-Bootcamp-with-Opensource-Tools</p>
        <h2>What You Will Learn</h2><p>Download different types of satellite remote sensing data for free<br>Have a thorough knowledge of remote sensing- theoretical concepts and applications<br>Implement pre-processing techniques using R and QGIS<br>Carry out the unsupervised classification of satellite remote sensing data<br>Carry out the supervised classification of satellite remote sensing data<br>Implement machine learning algorithms on satellite remote sensing data in R<br>Carry out habitat suitability mapping using remote sensing and machine learning<br>Use other freely available software tools such as Google Earth Engine and SNAP for RS data analysis</p>
        <h2>Audience</h2><p>This course is for people with prior experience of working spatial data such as GIS analysts, Ecologists, Forestry and Conservation Practioners, Geographers, and Geologists.</p>
        <h2>Approach</h2><p>This is an introductory course, i.e. we will focus on learning the most important and widely encountered remote sensing data processing and analyzing tasks in R, QGIS, GRASS and ESA-SNAP.</p>
        <h2>Key Features</h2><p>A good starter course to explain the fundamentals & properly understand the applications of remote sensing * Short lectures and practicals which are good to ensure the attention of the audience is still there.</p>
        <h2>Github Repo</h2><p>https://github.com/packtpublishing/satellite-remote-sensing-data-bootcamp-with-opensource-tools</p>
        <h2>About the Author</h2><h3>Minerva Singh</h3><p>Minerva Singh is a PhD graduate from Cambridge University where she specialized in Tropical Ecology. She is also a part-time Data Scientist. As part of her research, she must carry out extensive data analysis, including spatial data analysis. For this purpose, she prefers to use a combination of freeware tools: R, QGIS, and Python. She does most of her spatial data analysis work using R and QGIS. Apart from being free, these are very powerful tools for data visualization, processing, and analysis. She also holds an MPhil degree in Geography and Environment from Oxford University. She has honed her statistical and data analysis skills through several MOOCs, including The Analytics Edge and Statistical. In addition to spatial data analysis, she is also proficient in statistical analysis, machine learning, and data mining.</p>
        <h2>Course Outline</h2><h4>1. Introduction to Satellite Remote Sensing Data Analysis</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Introduction to the Course and Instructor</p><p style='margin: 0'>Introduction to Satellite Remote Sensing Data Analysis: Introduction to the Course and Instructor</p></td></tr><tr><td style='padding: 15px;'><p>2. What is Remote Sensing?</p><p style='margin: 0'>Introduction to Satellite Remote Sensing Data Analysis: What is Remote Sensing?</p></td></tr><tr><td style='padding: 15px;'><p>3. Different Types of Remote Sensing Data</p><p style='margin: 0'>Introduction to Satellite Remote Sensing Data Analysis: Different Types of Remote Sensing Data</p></td></tr><tr><td style='padding: 15px;'><p>4. Different Tools for Working with Remote Sensing-Start with R and QGIS</p><p style='margin: 0'>Introduction to Satellite Remote Sensing Data Analysis: Different Tools for Working with Remote Sensing-Start with R and QGIS</p></td></tr><tr><td style='padding: 15px;'><p>5. Get Started with SNAP Toolbox-Brief Introduction</p><p style='margin: 0'>Introduction to Satellite Remote Sensing Data Analysis: Get Started with SNAP Toolbox-Brief Introduction</p></td></tr><tr><td style='padding: 15px;'><p>6. Get Started with GRASS GIS-Brief Introduction</p><p style='margin: 0'>Introduction to Satellite Remote Sensing Data Analysis: Get Started with GRASS GIS-Brief Introduction</p></td></tr><tr><td style='padding: 15px;'><p>7. Conclusions to Section 1</p><p style='margin: 0'>Introduction to Satellite Remote Sensing Data Analysis: Conclusions to Section 1</p></td></tr></tbody></table><br><h4>2. Introduction to Optical Remote Sensing Data</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Principles Behind Collection of Optical Remote Sensing Data</p><p style='margin: 0'>Introduction to Optical Remote Sensing Data: Principles Behind Collection of Optical Remote Sensing Data</p></td></tr><tr><td style='padding: 15px;'><p>2. Different Types of Optical Remote Sensing Data</p><p style='margin: 0'>Introduction to Optical Remote Sensing Data: Different Types of Optical Remote Sensing Data</p></td></tr><tr><td style='padding: 15px;'><p>3. Downloading and Viewing Landsat Data</p><p style='margin: 0'>Introduction to Optical Remote Sensing Data: Downloading and Viewing Landsat Data</p></td></tr><tr><td style='padding: 15px;'><p>4. Different Landsat Sensors</p><p style='margin: 0'>Introduction to Optical Remote Sensing Data: Different Landsat Sensors</p></td></tr><tr><td style='padding: 15px;'><p>5. Downloading and Viewing Optical Data via QGIS</p><p style='margin: 0'>Introduction to Optical Remote Sensing Data: Downloading and Viewing Optical Data via QGIS</p></td></tr><tr><td style='padding: 15px;'><p>6. Conclusions to Section 2</p><p style='margin: 0'>Introduction to Optical Remote Sensing Data: Conclusions to Section 2</p></td></tr></tbody></table><br><h4>3. Pre-Processing Optical Data</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Why is Pre-Processing Needed for Optical Data?</p><p style='margin: 0'>Pre-Processing Optical Data: Why is Pre-Processing Needed for Optical Data?</p></td></tr><tr><td style='padding: 15px;'><p>2. Implementing Atmospheric Correction on Landsat Data in R</p><p style='margin: 0'>Pre-Processing Optical Data: Implementing Atmospheric Correction on Landsat Data in R</p></td></tr><tr><td style='padding: 15px;'><p>3. QGIS For Pre-Processing Landsat Data: Semi-Automatic Classification Plugin</p><p style='margin: 0'>Pre-Processing Optical Data: QGIS For Pre-Processing Landsat Data: Semi-Automatic Classification Plugin</p></td></tr><tr><td style='padding: 15px;'><p>4. Atmospherically Corrected Outputs from QGIS</p><p style='margin: 0'>Pre-Processing Optical Data: Atmospherically Corrected Outputs from QGIS</p></td></tr><tr><td style='padding: 15px;'><p>5. What Can Pre-Processed Satellite Data Be Used For?</p><p style='margin: 0'>Pre-Processing Optical Data: What Can Pre-Processed Satellite Data Be Used For?</p></td></tr><tr><td style='padding: 15px;'><p>6. Conclusions to Section 3</p><p style='margin: 0'>Pre-Processing Optical Data: Conclusions to Section 3</p></td></tr></tbody></table><br><h4>4. The Many Uses of Optical Data</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Stacking and Unstacking Bands in QGIS</p><p style='margin: 0'>The Many Uses of Optical Data: Stacking and Unstacking Bands in QGIS</p></td></tr><tr><td style='padding: 15px;'><p>2. Band Maths in R and QGIS</p><p style='margin: 0'>The Many Uses of Optical Data: Band Maths in R and QGIS</p></td></tr><tr><td style='padding: 15px;'><p>3. Texture Indices-Theory</p><p style='margin: 0'>The Many Uses of Optical Data: Texture Indices-Theory</p></td></tr><tr><td style='padding: 15px;'><p>4. Texture Indices-GRASS GIS</p><p style='margin: 0'>The Many Uses of Optical Data: Texture Indices-GRASS GIS</p></td></tr><tr><td style='padding: 15px;'><p>5. Texture Indices-ESA SNAP</p><p style='margin: 0'>The Many Uses of Optical Data: Texture Indices-ESA SNAP</p></td></tr><tr><td style='padding: 15px;'><p>6. Tasseled Cap Transformations-theory</p><p style='margin: 0'>The Many Uses of Optical Data: Tasseled Cap Transformations-theory</p></td></tr><tr><td style='padding: 15px;'><p>7. Tasseled Cap Transformations-GRASS GIS</p><p style='margin: 0'>The Many Uses of Optical Data: Tasseled Cap Transformations-GRASS GIS</p></td></tr><tr><td style='padding: 15px;'><p>8. Vegetation Indices in GRASS GIS</p><p style='margin: 0'>The Many Uses of Optical Data: Vegetation Indices in GRASS GIS</p></td></tr><tr><td style='padding: 15px;'><p>9. Vegetation Indices using RStoolbox</p><p style='margin: 0'>The Many Uses of Optical Data: Vegetation Indices using RStoolbox</p></td></tr><tr><td style='padding: 15px;'><p>10. Dimension Reduction-theory</p><p style='margin: 0'>The Many Uses of Optical Data: Dimension Reduction-theory</p></td></tr><tr><td style='padding: 15px;'><p>11. Dimension Reduction-QGIS</p><p style='margin: 0'>The Many Uses of Optical Data: Dimension Reduction-QGIS</p></td></tr><tr><td style='padding: 15px;'><p>12. Dimension Reduction-GRASS GIS</p><p style='margin: 0'>The Many Uses of Optical Data: Dimension Reduction-GRASS GIS</p></td></tr><tr><td style='padding: 15px;'><p>13. Conclusion to Section 4</p><p style='margin: 0'>The Many Uses of Optical Data: Conclusion to Section 4</p></td></tr></tbody></table><br><h4>5. Classification of Remote Sensing Satellite Data</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Theory of Unsupervised Classification</p><p style='margin: 0'>Classification of Remote Sensing Satellite Data: Theory of Unsupervised Classification</p></td></tr><tr><td style='padding: 15px;'><p>2. Unsupervised Classification-ESA SNAP</p><p style='margin: 0'>Classification of Remote Sensing Satellite Data: Unsupervised Classification-ESA SNAP</p></td></tr><tr><td style='padding: 15px;'><p>3. Theory of Supervised Classification</p><p style='margin: 0'>Classification of Remote Sensing Satellite Data: Theory of Supervised Classification</p></td></tr><tr><td style='padding: 15px;'><p>4. Supervised Classification in QGIS: Preliminary Steps</p><p style='margin: 0'>Classification of Remote Sensing Satellite Data: Supervised Classification in QGIS: Preliminary Steps</p></td></tr><tr><td style='padding: 15px;'><p>5. Classification and Post Classification Accuracy in QGIS</p><p style='margin: 0'>Classification of Remote Sensing Satellite Data: Classification and Post Classification Accuracy in QGIS</p></td></tr><tr><td style='padding: 15px;'><p>6. Machine Learning Theory</p><p style='margin: 0'>Classification of Remote Sensing Satellite Data: Machine Learning Theory</p></td></tr><tr><td style='padding: 15px;'><p>7. Create Training Data in QGIS</p><p style='margin: 0'>Classification of Remote Sensing Satellite Data: Create Training Data in QGIS</p></td></tr><tr><td style='padding: 15px;'><p>8. Apply Machine Learning Techniques on Satellite Data</p><p style='margin: 0'>Classification of Remote Sensing Satellite Data: Apply Machine Learning Techniques on Satellite Data</p></td></tr><tr><td style='padding: 15px;'><p>9. Conclusion to Section 5</p><p style='margin: 0'>Classification of Remote Sensing Satellite Data: Conclusion to Section 5</p></td></tr></tbody></table><br><h4>6. Introduction to Active Remote Sensing Data: Synthetic Aperture Radar</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Why Use Active Remote Sensing Data?</p><p style='margin: 0'>Introduction to Active Remote Sensing Data: Synthetic Aperture Radar: Why Use Active Remote Sensing Data?</p></td></tr><tr><td style='padding: 15px;'><p>2. Obtain ALOS PALSAR Data</p><p style='margin: 0'>Introduction to Active Remote Sensing Data: Synthetic Aperture Radar: Obtain ALOS PALSAR Data</p></td></tr><tr><td style='padding: 15px;'><p>3. Pre-processing of ALOS PALSAR data</p><p style='margin: 0'>Introduction to Active Remote Sensing Data: Synthetic Aperture Radar: Pre-processing of ALOS PALSAR data</p></td></tr><tr><td style='padding: 15px;'><p>4. Filtering for Speckles</p><p style='margin: 0'>Introduction to Active Remote Sensing Data: Synthetic Aperture Radar: Filtering for Speckles</p></td></tr><tr><td style='padding: 15px;'><p>5. Obtain back-scatter values from ALOS PALSAR data</p><p style='margin: 0'>Introduction to Active Remote Sensing Data: Synthetic Aperture Radar: Obtain back-scatter values from ALOS PALSAR data</p></td></tr></tbody></table>

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Pre-process and Analyze Satellite Remote Sensing Data with Free Software

Satellite Remote Sensing Data Bootcamp With Opensource Tools

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Python EVENINGS Course
Basic Python syntax and principles of object-oriented programming. 
Most attendees are in-work IT Professional. 
Private individuals are also very welcome. 
Evening courses also running. 

Details:
Our Style: Hands-on, Practical 
Location: Online, Instructor-led 
Download: anaconda.com 
Duration: 4 weeks, 1 evening per week, 6pm - 8pm 
Times: arrange a time for your time zone 
How to attend:  
Connection Link For the course: https://meet.goto.com/910697125
Once you have made the payment, use the above link on the date booked, to connect with the trainer. 
Python Basics EVENINGS Course
 This Python course London Evening covers the essential Python Basics, in our interactive, instructor led Live Virtual Classroom. This Python Basics course is a very good introduction to essential fundamental programming concepts using Python as programming language. These concepts are daily used by programmers and is your first step to working as a programmer. By the end, you'll be comfortable in programming Python code. You will have done small projects. This will serve for you as examples and samples that you can use to build larger projects. You can publish your code online to keep as a portfolio. 

This Python Programming course is hands-on and practical, to give you in-depth, practical experience of the topics covered. 
Week 1: Basics
 Python Data Types and Variables: 
Primitive Data types; Working with variables and its scope; Conversion and casting types in Python. 
 Operators and Expressions:  
 Introduction of operators; Arithmetic operators; Relational operators; Assignment operator; Logical operators; Increment and decrement operators. 
 Decision Making: 
If statement; If - else statement; If- elif - else statement; Nested if - else. 
Using Loops: 
The while, while-else. 
For loop; 
Jump statements: break, continue; 
Nesting loops. 
Week 2: Data Structures & Database
Lists.  
Tuples. 
Sets. 
Dictionary. Nested Dictionary. 
Json Files. 
Reading csv and text files
Connecting with a database and run SQL Queries. 
Week 3: Python built-in functions &  Pandas Dataframe Basics
 
Using built-in modules and functions: 
Strings Functions. 
Maths Functions. 
Random Functions. 
Data Frames; 
Getting data into a dataframe: 
Dict to Dataframe, Dataframe to Dict.  
Dataframe basics: 
Slicing Dataframes, 
Getting information about the dataframe, 
Filter and query a Dataframes, 
Working with null-values.
Week 4: OOP: Using Modules, functions, classes
 Creating and using custom Functions. 
Creating functions; 
Using parameters and return values; 
 
Introduction to Classes and Objects: 
Creating a Class; 
Creating an Object; Using an Object; 
Adding instance variables; controlling accessibility; and naming conventions for class members. 
 Class Constructors; Parameterized Constructors. 
Inheritance. Overload. 

What is included
PCWorkshops Course Certificate on completion
Python Course Notes
Python Code Examples
Practical Python Course exercises and Code Samples
After the course: 1-Hour personalised online revision session
  

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Python

Basic Python syntax and principles of Object Orientated Programming. 
Most attendees are in-work IT Professional. 
Private individuals are also very welcome. 
Evening courses also running. 
Our Style: Hands-on, Practical 
Location: Online, Instructor-led 
Download: anaconda.com 
Duration: 6 weeks, 1 evening per week, 6pm - 8pm 
Times: arrange a time for your time zone 

Python EVENINGS Course, Online Instructor-led

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<div style="color: rgb(57, 54, 79); box-sizing: border-box;" id="isPasted" fr-original-style=" color: rgb(57, 54, 79);"><div data-testid="summary" id="isPasted" fr-original-style="" style="box-sizing: border-box;"><div data-testid="summary" id="isPasted" fr-original-style="" style="box-sizing: border-box;"><div data-testid="summary" id="isPasted" fr-original-style="" style="box-sizing: border-box;"><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">This Python BootCamp is Instructor-led, Practical. In the12-week Python course, learn start to in-depth, leading to a good Python career.</strong></p></div><div data-testid="organizerBrief" fr-original-style="" style="box-sizing: border-box;"><div data-testid="creator-signal-main-section" fr-original-style="" style="box-sizing: border-box;"><section fr-original-style="" style="box-sizing: border-box;"><br fr-original-style="" style="box-sizing: border-box;"></section></div></div></div><div data-testid="organizerBrief" fr-original-style="" style="box-sizing: border-box;"><div data-testid="creator-signal-main-section" fr-original-style="" style="box-sizing: border-box;"><section fr-original-style="" style="box-sizing: border-box;"><br fr-original-style="" style="box-sizing: border-box;"></section></div></div></div><hr fr-original-style="" style="border-color: var(--border-muted); border-style: solid; clear: both; break-after: page; user-select: none; box-sizing: border-box;"><div style="color: rgb(57, 54, 79); box-sizing: border-box;" id="isPasted" fr-original-style=" color: rgb(57, 54, 79);"><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">PYTHON BOOTCAMP:</strong></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">This 12-week Python Boot Camp is a practical, instructor-lead program, covering Python from start to in-depth. You will be fully fluent and confident as a Python programmer.</strong></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);">If you have more questions goto&nbsp;<a href="http://pcworkshopslondon.co.uk/contact.html" target="_blank" rel="nofollow noopener noreferrer" data-airgap-id="66" style="color: var(--eds-control,#3659e3); user-select: auto; font-size: var(--font-size); box-sizing: border-box; cursor: pointer; text-decoration: inherit;" fr-original-style=" color: var(--eds-control,#3659e3);">https://pcworkshopslondon.co.uk/contact.html&nbsp;</a>,</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);">Or&nbsp;<a href="https://pcworkshopslondon.co.uk/" target="_blank" rel="nofollow noopener noreferrer" data-airgap-id="67" style="color: var(--eds-control,#3659e3); user-select: auto; font-size: var(--font-size); box-sizing: border-box; cursor: pointer; text-decoration: inherit;" fr-original-style=" color: var(--eds-control,#3659e3);">contact us on training@pcworkshopslondon.co.uk</a></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><a href="https://pcworkshopslondon.co.uk/contact.htm" target="_blank" rel="nofollow noopener noreferrer" data-airgap-id="68" style="color: var(--eds-control,#3659e3); user-select: auto; font-size: var(--font-size); box-sizing: border-box; cursor: pointer; text-decoration: inherit;" fr-original-style=" color: var(--eds-control,#3659e3);">C﻿ustomise dates, course outline, arrange installments</a></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);">This course will give you enough&nbsp;<strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">practical experience and practical projects</strong>&nbsp;to code, to give you full confidence to enter into the coding profession. &nbsp;&nbsp;</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Duration:&nbsp;</strong>3 months:</p><ul style="color: rgb(111, 114, 135); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><li fr-original-style="" style="box-sizing: border-box;">1 Python class per week,</li><li fr-original-style="" style="box-sizing: border-box;">Plus pratical work,</li><li fr-original-style="" style="box-sizing: border-box;">Plus personal trainer-mentor for 1-1 training,</li><li fr-original-style="" style="box-sizing: border-box;">Plus e-learning materials.</li></ul><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Final project :&nbsp;</strong>Practical to upload to&nbsp;<strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">GitHub&nbsp;</strong>and show-case</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Date and times, choose:</strong></p><ul style="color: rgb(111, 114, 135); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Fridays in London or Online&nbsp;</strong>, 10am - 5pm,</li><li fr-original-style="" style="box-sizing: border-box;">or&nbsp;<strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Saturdays in London or Online&nbsp;</strong>, 12noon-6pm,</li><li fr-original-style="" style="box-sizing: border-box;">o﻿r negotiate your date</li></ul><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Study level:</strong> Start from beginners level to in-depth, ready to work professionally.</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Virtual attendance: &nbsp;</strong>online instructor-led&nbsp;</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Download</strong>: Anaconda.com</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Pre-requisites:&nbsp;</strong>General computer literacy.</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Oracle Qualification:&nbsp;</strong>PCWorkshops Python Programmer Certificate</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Payments:</strong>&nbsp; You may apply to pay in installments for this Python Training course</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">COURSE OUTLINE</strong></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">W﻿eek 1 - 4: Essentials</strong></p><ol fr-original-style="" style="box-sizing: border-box;"><li fr-original-style="" style="box-sizing: border-box;">Python Coding Basics</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Object Oriented programming:&nbsp;</strong>Python Object Orientated programming (OOP)</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">UX Principles:&nbsp;</strong>UX Principles and applying it on Front-ends with TKinter</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Specialised topics:&nbsp;</strong>Dates, Localization, Strings, Maths Operation , Random Number,&nbsp;<strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Lambdas</strong></li></ol><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">W﻿eek 5 - 10 : All about data</strong></p><ol fr-original-style="" style="box-sizing: border-box;"><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Python Data Structures:</strong>&nbsp;Lists, Tuples, Sets,&nbsp;<strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Exceptions</strong>, I/O Fundamentals , Reading and Writing file</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Database:&nbsp;</strong>Database principles and SQL.&nbsp;<strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Database Project:&nbsp;</strong>Python database connections and creating a database driven project</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Data Analytics:&nbsp;</strong>Numpy. Pandas for data analytics and data queries.</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Data Analytics:&nbsp;</strong>Pandas data cleaning and restructuring, interacticting with Excel, Csv, Json,etc.</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Data visualisation:&nbsp;</strong>MatPlotLib</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Prediction:&nbsp;</strong>Machine Learning Basics</li></ol><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">W﻿eek 11 and 12: The final touch</strong></p><ol fr-original-style="" style="box-sizing: border-box;"><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Python Concurrency and Multi-threading:</strong>&nbsp;Threads vs. Processes, Threading Module, Threading Event, Stop a Thread, Daemon Threads, Thread-safe Queue, Thread Pools, Locks</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Python Unit Testing</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">O﻿ptional&nbsp;</strong>: Replace Week 11 or 12 with Scraping using Python, ot Tkinter Front-ends</li></ol><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">I﻿NCLUDED:</strong></p><ul style="color: rgb(111, 114, 135); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><li fr-original-style="" style="box-sizing: border-box;">PCWorkshops Python Course Certificate on completion.</li><li fr-original-style="" style="box-sizing: border-box;">Python Course notes.</li><li fr-original-style="" style="box-sizing: border-box;">Practical Course exercises, Code Examples, Online Materials.</li><li fr-original-style="" style="box-sizing: border-box;">After the course, continuous assistance with practical and preparation for exams</li><li fr-original-style="" style="box-sizing: border-box;">Max group size on this is 4.</li><li fr-original-style="" style="box-sizing: border-box;">Portfolio: Post your Python project online.</li><li fr-original-style="" style="box-sizing: border-box;">Exam preparation and interview questions</li></ul><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">MORE ABOUT THE ONLINE CLASSROOM</strong></p><ul style="color: rgb(111, 114, 135); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><li fr-original-style="" style="box-sizing: border-box;">&nbsp;Attend from your internet connection</li><li fr-original-style="" style="box-sizing: border-box;">&nbsp;Instructor-led, get instant answers to your questions</li><li fr-original-style="" style="box-sizing: border-box;">&nbsp;Fully interactive</li><li fr-original-style="" style="box-sizing: border-box;">&nbsp;Work clearly explained with demonstrations and examples</li><li fr-original-style="" style="box-sizing: border-box;">&nbsp;Practical exercises to be tried out by delegate</li></ul><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">WHAT YOU WILL GAIN:</strong></p><ul style="color: rgb(111, 114, 135); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><li fr-original-style="" style="box-sizing: border-box;">Skills &amp; knowledge: Python coding knowledge and understanding with good practical application &nbsp;</li><li fr-original-style="" style="box-sizing: border-box;">Certification:&nbsp;Internal PCWorkshops Python certificate</li><li fr-original-style="" style="box-sizing: border-box;">Portfolio: You will have an online portfolio of Python projects&nbsp;</li><li fr-original-style="" style="box-sizing: border-box;">Experience:&nbsp;Our comprehensive practical makes you job ready</li></ul></div><div data-testid="image-content" style="color: rgb(57, 54, 79); box-sizing: border-box;" fr-original-style=" color: rgb(57, 54, 79);"><img src="https://img.evbuc.com/https%3A%2F%2Fcdn.evbuc.com%2Fimages%2F444528299%2F44980801875%2F1%2Foriginal.20230212-111230?h=2000&w=720&auto=format%2Ccompress&q=75&sharp=10&s=bc03bf9766e6c9ca0436ac60d0be83d6" alt="" data-airgap-id="88" fr-original-style="" style="cursor: pointer; padding: 0px 1px; user-select: none; max-width: 100%; position: relative; box-sizing: border-box;" fr-original-class="fr-draggable"></div><div data-testid="image-content" style="color: rgb(57, 54, 79); box-sizing: border-box;" fr-original-style=" color: rgb(57, 54, 79);"><img src="https://img.evbuc.com/https%3A%2F%2Fcdn.evbuc.com%2Fimages%2F588336959%2F44980801875%2F1%2Foriginal.20230901-170557?h=2000&w=720&auto=format%2Ccompress&q=75&sharp=10&s=e4036ff76e1af36cfba9452461b16c48" alt="" data-airgap-id="87" fr-original-style="" style="cursor: pointer; padding: 0px 1px; user-select: none; max-width: 100%; position: relative; box-sizing: border-box;" fr-original-class="fr-draggable"></div><div data-testid="image-content" style="color: rgb(57, 54, 79); box-sizing: border-box;" fr-original-style=" color: rgb(57, 54, 79);"><img src="https://img.evbuc.com/https%3A%2F%2Fcdn.evbuc.com%2Fimages%2F588337149%2F44980801875%2F1%2Foriginal.20230901-170614?h=2000&w=720&auto=format%2Ccompress&q=75&sharp=10&s=cdf1fcea5ad47abc354df67b458d5237" alt="" data-airgap-id="89" fr-original-style="" style="cursor: pointer; padding: 0px 1px; user-select: none; max-width: 100%; position: relative; box-sizing: border-box;" fr-original-class="fr-draggable"></div><div data-testid="image-content" style="color: rgb(57, 54, 79); box-sizing: border-box;" fr-original-style=" color: rgb(57, 54, 79);"><img src="https://img.evbuc.com/https%3A%2F%2Fcdn.evbuc.com%2Fimages%2F588337349%2F44980801875%2F1%2Foriginal.20230901-170630?h=2000&w=720&auto=format%2Ccompress&q=75&sharp=10&s=839d02fa3087d55ac858bcbb697972f5" alt="" data-airgap-id="86" fr-original-style="" style="cursor: pointer; padding: 0px 1px; user-select: none; max-width: 100%; position: relative; box-sizing: border-box;" fr-original-class="fr-draggable"></div></div><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><br fr-original-style="" style="box-sizing: border-box;"></p><div style="color: rgb(30, 10, 60); box-sizing: border-box;" id="isPasted" fr-original-style=" color: rgb(30, 10, 60);"><hr fr-original-style="" style="border-color: var(--border-muted); border-style: solid; clear: both; break-after: page; user-select: none; box-sizing: border-box;"><h2 fr-original-style="" style="box-sizing: border-box;">Refund Policy</h2></div><div style="color: rgb(111, 114, 135); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);">No Refunds</div>

This Python Data Analytics BootCamp is Instructor-led, Practical. In the12-week Python course, learn start to in-depth, leading to a good Python career.



PYTHON BOOTCAMP:
This 12-week Python Data Analytics Data Boot Camp is designed to give you a complete skill set required by data analysts .
You will be fully fluent and confident as a Python  data analyst, with full understanding of Python Programming.
From Data, databases, datasets, importing, cleaning, transforming, analysing to visualisation and creating awesome dashboards
The course is a practical, instructor-lead program.

If you have more questions goto https://pcworkshopslondon.co.uk/contact.html,
Or contact us on training@pcworkshopslondon.co.uk
C﻿ustomise dates, course outline, arrange installments
This course will give you enough practical experience and practical projects to code, to give you full confidence to enter into the coding profession. 
Duration: 3 months, 12 weeks:
1 Python class per week,
Plus practical work,
Plus personal trainer-mentor for 1-1 training,
Plus e-learning materials.
Final project : Practical to upload to GitHub and show-case
Date and times, choose:
Fridays in London or Online , 10am - 5pm,
or Saturdays in London or Online , 12noon-6pm,
o﻿r negotiate your date
Study level: Start from beginners level to in-depth, ready to work professionally.
Virtual attendance: online instructor-led 
Download: Anaconda.com
Pre-requisites: General computer literacy.
Oracle Qualification: PCWorkshops Python Programmer Certificate
Payments: You may apply to pay in installments for this Python Training course
COURSE OUTLINE
W﻿eek 1 - 4: Essentials
Python Coding Basics
Object Oriented programming: Python Object Orientated programming (OOP)
UX Principles: UX Principles and applying it on Front-ends with TKinter
Specialised topics: Dates, Localization, Strings, Maths Operation , Random Number, Lambdas
W﻿eek 5 - 10 : All about data
Python Data Structures: Lists, Tuples, Sets, Exceptions, I/O Fundamentals , Reading and Writing file
Database: Database principles and SQL. Database Project: Python database connections and creating a database driven project
Data Analytics: Numpy. Pandas for data analytics and data queries.
Data Analytics: Pandas data cleaning and restructuring, interacticting with Excel, Csv, Json,etc.
Data visualisation: MatPlotLib
Prediction: Machine Learning Basics
W﻿eek 11 and 12: The final touch
Python Concurrency and Multi-threading: Threads vs. Processes, Threading Module, Threading Event, Stop a Thread, Daemon Threads, Thread-safe Queue, Thread Pools, Locks
Python Unit Testing
O﻿ptional : Replace Week 11 or 12 with Scraping using Python, ot Tkinter Front-ends
I﻿NCLUDED:
PCWorkshops Python Course Certificate on completion.
Python Course notes.
Practical Course exercises, Code Examples, Online Materials.
After the course, continuous assistance with practical and preparation for exams
Max group size on this is 4.
Portfolio: Post your Python project online.
Exam preparation and interview questions
MORE ABOUT THE ONLINE CLASSROOM
Attend from your internet connection
Instructor-led, get instant answers to your questions
Fully interactive
Work clearly explained with demonstrations and examples
Practical exercises to be tried out by delegate
WHAT YOU WILL GAIN:
Skills & knowledge: Python coding knowledge and understanding with good practical application
Certification: Internal PCWorkshops Python certificate
Portfolio: You will have an online portfolio of Python projects
Experience: Our comprehensive practical makes you job ready






Refund Policy
No Refunds

PYTHON BOOTCAMP:



This 12-week Python Data Analytics Data Boot Camp is designed to give you a complete skill set required by data analysts .



You will be fully fluent and confident as a Python  data analyst, with full understanding of Python Programming.



From Data, databases, datasets, importing, cleaning, transforming, analysing to visualisation and creating awesome dashboards



The course is a practical, instructor-lead program.



Python Data Analytics BootCamp, 12-weeks, Online Instructor-led

Python Bootcamp Saturdays, Online

<article>
					<div>
						<h5>Python Beginners Course, 1-Day.</h5>
					</div>
					<div></div>
					<p>
						<span> </span>
						<br />This course covers the essential Python Basics, in our interactive, instructor led Live Virtual Classroom.
						<br />	This Python Basics course is a very good introduction to essential fundamental programming concepts using Python as programming language.
							<br />These concepts are daily used by programmers and is your first step to working as a programmer.
							<br />By the end, you'll be comfortable in programming Python code.
							<br />You will have done small projects.
							<br />This will serve for you as examples and samples that you can use to build larger projects.
						 
						<br /><b>Location: </b>Instructor-led, Online.
						<br /><b>Our Style: </b>Hands-on, Practical Course.
						<br /><b>Group Size: </b>Max 4 people per group.  
						<br /><b>Qualification: </b>PCWorkshops Beginners Certification
						<br /><b>Hours: </b>1 Day, 10am-5pm
						<br /><b>Download: </b>anaconda.com
						
				  	</p>
	    		</article> 
				
				<article>
					<div>
						<h5>Python Beginners Course, Course Outline.</h5>
					</div>
					<div></div>
					<p>
						<span> </span>
						<br />
						<b>Session 1: Basics</b>
 
						<br />Python Data Types and Variables:
						Working with variables and its scope; Conversion and casting types in Python.
						<br />Operators and Expressions.
						 

						<br />Decision Making: If statement; If - else statement; If- elif - else statement; Nested if - else. 
						
						<br />Using Loops: The while, while-else. For loop; Jump statements: break, continue; Nesting loops.
<br />
						<br /><b>Session 2: Data Structures</b>
						 
						<br />Lists.
						<br />Tuples.
						<br />Sets.
						<br />Dictionary. Nested Dictionary.
						<br />Json Files.
<br />
						<br /><b>Session 3: Python Built-in functions</b> 
						<br />Strings Functions. 
						<br />Maths Functions.
						<br />Random Functions.
						<br />Python Date functions.
<br />
						<br /><b>Session 4: OOP: Using Modules, functions, classes</b>
						 
						<br />Creating and using custom Functions.
						
						<br />Using parameters and return values.

						<br />Introduction to Classes and Objects:
						<br />Creating a Class. Creating and using Objects. 
						<br />Class Constructors.
						<br />Inheritance. Overload.
<br />
						<br /><b>Session 5: Access SQL Database Via Python</b>
						 
						<br /><b>Connection details:</b> Connect to a database using access codes.
						<br /><b>Select Queries:</b> Retrieving records and iterating results sets, using variables and parameters in queries.
						<br /><b>Working with DDL comands: </b>Create a database, drop a database. Create a table, alter tables, drop a table.
						<br /><b>Working with DML Commands: </b>Insert, delete, update records.

						<br /><br /><br /><b>Session 6: Pandas Dataframe Basics</b>
						 
						<br />Getting data into a dataframe:
						<br />Dict to Dataframe, Dataframe to Dict.
						<br />Excel To Dict, Dict to Excel , working with Excel data, multiple Excel sheets.
						<br />Dataframe basics:
						<br />Slicing Dataframes, Querying, filter and sort a dataframe,
						
						<br />Working with duplicates and null-values, Sampling, Group by, Join.
						
						
						
				  	</p>
	    		</article> 

			    <div>  
				     
	     
	               <div id="cincluded">
	                  <div>
	                     <h5>Python Beginners Course Materials</h5>
	                  </div>

	                  <article>
	                  <div>
	                     <ul>
	                        <li>Python Beginners Certificate on completion  </li>
							                  
						    <li>Python Beginners Notes</li>
							<li>Python Code Examples</li>
	                        <li>Practical Python Beginners exercises</li>
	                        
	                     </ul>
	                  </div>
						   
	                  </article>
	               </div>
			
				    <article>
					<div>
						<h5>More about Python</h5>
					</div>
					<div></div>
					<p>
							Python is the Easiest Programming Language to Learn 
				 				Anybody can learn how to use it and  entry-level coders get access to the industry in a 
									fast-tacked manner and can from there migrate to other languages.
								 <br />
								 Learning to code  is now more important than ever, since a growing number of application and <br />
								  digital products require programmers. <br />

								 Additionally, as an interpreted coding language, Python allows you to run each line of code <br />
								 after writing it, rather 
								 than other compiled languages, such as C++. <br />
								 This is particularly useful for beginners, as they can test their work and 
								  gain instant feedback, <br />
								  to make amendments where required and continuously improve. A Python Course will
								explain to you how to do this<br />
								  <br />
								 Python is a Versatile Coding Language <br />
								 Use it for : <br /> 
								 Data mining ,  Data analytics , Data visualisation ,  AI and machine learning,  Building apps ,
								 Web development and web application development ,  Developing games,  Quantitative and qualitative analysis,
								 Data Engineering,  A Python Course is the start of all of the above.
								 <br /><br />
								 Learning Python will Improve Your Job Prospects <br />
								 As the fastest-growing computer programming language in the world, 
								 Python is also one of the most in-demand jobs. According to 2022 LinkedIn data,   
								Python is the second most in-demand programming language, after Java.  
								All of this makes a Python Course essential. 
				  	</p>
	    		</article> 
					  
				    
					
					
					
				   <div id="booking">
	                  <div>
	                     <h5>Book the Python Beginners Course</h5>
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 							<div id="eventbrite-widget-container-48024956939"></div>

							

							
							 
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				   <div id="cincluded">
	                  <div>
	                     <h5>About us</h5>
	                  </div> 
	                  	<article>
					    <div>
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					    		<div>
					    			
					    			<h5>Our experienced trainers are award winners. </h5> 
					    			<ul>
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											More about us
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											FAQ's
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Python Beginners Course, 1-Day.
   
This course covers the essential Python Basics, in our interactive, instructor led Live Virtual Classroom. 
	This Python Basics course is a very good introduction to essential fundamental programming concepts using Python as programming language. 
These concepts are daily used by programmers and is your first step to working as a programmer. 
By the end, you'll be comfortable in programming Python code. 
You will have done small projects. 
This will serve for you as examples and samples that you can use to build larger projects. 

Location: Instructor-led, Online. 
Our Style: Hands-on, Practical Course. 
Group Size: Max 4 people per group. 
Qualification: PCWorkshops Beginners Certification 
Hours: 1 Day, 10am-5pm 
Download: anaconda.com 
Python Beginners Course, Course Outline.
  Session 1: Basics 
Python Data Types and Variables: Working with variables and its scope; Conversion and casting types in Python. 
Operators and Expressions. 
Decision Making: If statement; If - else statement; If- elif - else statement; Nested if - else. 
Using Loops: The while, while-else. For loop; Jump statements: break, continue; Nesting loops.

 
Session 2: Data Structures 
Lists. 
Tuples. 
Sets. 
Dictionary. Nested Dictionary. 
Json Files.

 
Session 3: Python Built-in functions 
Strings Functions. 
Maths Functions. 
Random Functions. 
Python Date functions.

 
Session 4: OOP: Using Modules, functions, classes 
Creating and using custom Functions. 
Using parameters and return values. 
Introduction to Classes and Objects: 
Creating a Class. Creating and using Objects. 
Class Constructors. 
Inheritance. Overload.

 
Session 5: Access SQL Database Via Python 
Connection details: Connect to a database using access codes. 
Select Queries: Retrieving records and iterating results sets, using variables and parameters in queries. 
Working with DDL comands: Create a database, drop a database. Create a table, alter tables, drop a table. 
Working with DML Commands: Insert, delete, update records. 


Session 6: Pandas Dataframe Basics 
Getting data into a dataframe: 
Dict to Dataframe, Dataframe to Dict. 
Excel To Dict, Dict to Excel , working with Excel data, multiple Excel sheets. 
Dataframe basics: 
Slicing Dataframes, Querying, filter and sort a dataframe, 
Working with duplicates and null-values, Sampling, Group by, Join. 
Python Beginners Course Materials
Python Beginners Certificate on completion
Python Beginners Notes
Python Code Examples
Practical Python Beginners exercises
More about Python
 Python is the Easiest Programming Language to Learn Anybody can learn how to use it and entry-level coders get access to the industry in a fast-tacked manner and can from there migrate to other languages. 
 Learning to code is now more important than ever, since a growing number of application and 
 digital products require programmers. 
 Additionally, as an interpreted coding language, Python allows you to run each line of code 
 after writing it, rather than other compiled languages, such as C++. 
 This is particularly useful for beginners, as they can test their work and gain instant feedback, 
 to make amendments where required and continuously improve. A Python Course will explain to you how to do this
 
 Python is a Versatile Coding Language 
 Use it for : 
 Data mining , Data analytics , Data visualisation , AI and machine learning, Building apps , Web development and web application development , Developing games, Quantitative and qualitative analysis, Data Engineering, A Python Course is the start of all of the above. 

 Learning Python will Improve Your Job Prospects 
 As the fastest-growing computer programming language in the world, Python is also one of the most in-demand jobs. According to 2022 LinkedIn data, Python is the second most in-demand programming language, after Java. All of this makes a Python Course essential. 
 

Programming Languages

his course covers the essential Python Basics, in our interactive, instructor led Live Virtual Classroom. 
	This Python Basics course is a very good introduction to essential fundamental programming concepts using Python as programming language. 
These concepts are daily used by programmers and is your first step to working as a programmer. 
By the end, you'll be comfortable in programming Python code. 
You will have done small projects. 
This will serve for you as examples and samples that you can use to build larger projects. 

Python Beginners Course, 1-Day

<article>
<div>
<h5>Python Data Analytics Course</h5>
</div>
<div></div>
<p>  						 
	</p><div>
	<ul>
		
<div>
    <div id="widget-reviews"><div><h3>Python Beginners Course</h3><div><span></span><span></span><span></span><span></span><span></span><div>(4.6)</div></div><span></span><br /><div>Based on 5 reviews</div><div><div><div id="previous"><i></i></div><div id="currentReview"><div> Excellent course, led by a knowledg</div><div> Excellent course, led by a knowledgeable and engaging instructor. I attended ...</div><div> Helen S</div></div><div id="next"><i></i></div></div></div></div></div>
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		<p>
		<b>Python Data Course. </b>Data Analytics with Python using Numpy, Pandas, Dataframes. 
		<br />Most attendees are in-work Data Professional.
		<br />Private individuals are very welcome. 
		<br /><b>Our Style: </b>Hands-on, Practical  
		<br /><b>Location:  </b>Online, Instructor-led  
		<br /><b>Download:  </b>anaconda.com
		<br /><b>Duration:  </b>2 consecutive days, 10am - 5pm
		<br /><b>Times: </b>arrange a time for your time zone
	    </p>
	</ul>	

<p></p>
</div></article>

<div>
	  <div>
			<h5>Python Data Analytics Course </h5>
	  </div>
	  <div></div>
	  <p>  
	  <br /> 
	  </p>
	<div>
	<h5>Session 1: Database: </h5>
	</div>
	<div></div>
	<div> 
					<p>  <strong>SQLite3:</strong>  
					<br /> Linking with SQL Database.
					<br /> Create, Amend and Drop Tables.
					<br /> Insert, Update and delete records.
					<br /> Select queries.
					<br /> Traverse and display query results.
					<br /> Using parameters in queries.
					<br /> Get metadata about tables and columns. 
					</p> 
			</div>
	<div>
	<h5>Session 2: Data Structures</h5>
	</div> <div></div>
	<div> 
				<p> <strong>Data Structures:</strong>  
					<br />Tuples.
					<br />Sets.
					<br />Dictionary. Nested Dictionary.
					<br />Json Files.
				</p>
			</div>
	<div>
	<h5>Session 3: Python Numpy</h5>
	</div> <div></div>
	<div> 
				<p>  <strong>Numpy:</strong>  
				<br />The Python NumPy Module:
				<br />Working with arrays, create data using arrays.
				<br />Array manipulation.
				<br />String functions on arrays. 
				<br />Math, arithmetic and statistical functions.
				
				</p>
			</div>
	<div>
	<h5>Session 4: Python Pandas Dataframes and data importing</h5>
	</div> <div></div>
	<div>
		<p>  <strong>Python Dataframes</strong>  
		<br /> Data Series. Date/ Time Functionality. Time series.
		<br /> Creating Dataframes, Indexing. 
		<br />Dict to Dataframe, Dataframe to Dict.
		<br />Csv to Dataframe, Dataframe to csv.
		<br />Excel to Dataframe, Dataframe to Excel.
		</p>
	</div>

	<div>
	<h5>Session 5: Data Cleaning and preparation</h5>
	</div> <div></div>
	<div>	 
		<p> <strong>Data Cleaning and preparation</strong>  
		<br />Finding, replacing and filtering missing data.
		<br />Remove Duplicates.
		<br />Replacing values.
		<br />Renaming Axis Indexes.
		</p>
	</div>
	
	<div>
	<h5>Session 6: Pandas Data Wrangling</h5>
	</div> <div></div>
	<div>	 
		<p> <strong>Data Wrangling:</strong>   
		
		<br />Indexing, Re-indexing, 
		<br />Reorder, 
		<br />Sorting, Stastitics, 
			<br />Transforming data using  
		<br />Dataframe Joins, Merging, Concatenation, Overlap, Append, zip. 
		 
		</p>
	</div>
	
	<div>
	<h5>Week 6: Pandas Data Analysis</h5>
	</div> <div></div>
	<div>	 
		<p> <strong>Data Analysis:</strong>   
		<br /> Sorting. 
		<br /> Analysing and finding data using filter, slicing and dataframe queries. 
		<br /> Finding data by Iteration.
		<br /> Find statistics: Functions, Aggregate functions. 
		<br /> Unique values.
		<br />String objects, Regex. 
		</p>
	</div>
</div>
 

<div>   

	   <div id="cincluded">
		  <div>
			 <h5>Included with the Python Course</h5>
		  </div>

		  <article>
		  <div>
			 <ul>
				<li>PCWorkshops Course Certificate on completion  </li>
									   
				<li>Python Course Notes</li>
				<li>Python Code Examples</li>
				<li>Practical Python Course exercises and Code Samples</li>
				<li>After the course: 1-Hour personalised online revision session</li>
			 </ul>
		  </div>
		  </article>
	   </div>
				    
<div>
	                  <div>
	                     <h5 id="cincluded2">Book the Python Course</h5>
	                  </div>
 
	 
		<div id="eventbrite-widget-container-48025096356"></div>
		
		  		
					
					 
</div>
				   <div id="caboutus">
	                  <div>
	                     <h5>About us</h5>
	                  </div> 
	                  	<article>
					    <div>
					    	<div>
					    		<div>
					    			
					    			<h5>Our experienced trainers are award winners. </h5> 
					    			<ul>
										<li>
											More about us
										</li>
										<li>
											FAQ's
										</li>
										<li>
											Client Comments  
										</li>
									 </ul>
					    		</div>
					    		<div>
					    			
					    				
					    			
					    		</div>
					    	</div>
	                     
					    </div>
					    </article>						
	               </div>
				   
				   
	        </div>

Python Data Analytics Course

Python Data Analytics with Python using 
Numpy, 
Pandas, Dataframes. 

Most attendees are in-work Data Professional.  Private individuals are very welcome. 
Our Style: Hands-on, Practical 
Location: Online, Instructor-led 
Download: anaconda.com 
Duration: 1 consecutive day, 11am-5pm
Dates Times: You may let us know which dates your would prefer, or attend as scheduled

Python Data Analytics Course Description
  
Session 1: Database:
 SQLite3: 
 Linking with SQL Database. 
 Create, Amend and Drop Tables. 
 Insert, Update and delete records. 
 Select queries. 
 Traverse and display query results. 
 Using parameters in queries. 
 Get metadata about tables and columns. 
Session 2: Data Structures
 Data Structures: 
Tuples. 
Sets. 
Dictionary. Nested Dictionary. 
Json Files. 
Session 3: Python Numpy
 Numpy: 
The Python NumPy Module: 
Working with arrays, create data using arrays. 
Array manipulation. 
String functions on arrays. 
Math, arithmetic and statistical functions. 
Session 4: Python Pandas Dataframes and data importing
 Python Dataframes 
 Data Series. Date/ Time Functionality. Time series. 
 Creating Dataframes, Indexing. 
Dict to Dataframe, Dataframe to Dict. 
Csv to Dataframe, Dataframe to csv. 
Excel to Dataframe, Dataframe to Excel. 
Session 5: Data Cleaning and preparation
 Data Cleaning and preparation 
Finding, replacing and filtering missing data. 
Remove Duplicates. 
Replacing values. 
Renaming Axis Indexes. 
Session 6: Pandas Data Wrangling
 Data Wrangling: 
Indexing, Re-indexing, 
Reorder, 
Sorting, Stastitics, 
Transforming data using 
Dataframe Joins, Merging, Concatenation, Overlap, Append, zip. 
Week 6: Pandas Data Analysis
 Data Analysis: 
 Sorting. 
 Analysing and finding data using filter, slicing and dataframe queries. 
 Finding data by Iteration. 
 Find statistics: Functions, Aggregate functions. 
 Unique values. 
String objects, Regex. 
Included with the Python Course
PCWorkshops Course Certificate on completion
Python Course Notes
Python Code Examples
Practical Python Course exercises and Code Samples
After the course: 1-Hour personalised online revision session
 

Pandas

Python Data Analytics with Python using 



Numpy, 




Pandas, Dataframes. 





Most attendees are in-work Data Professional.  Private individuals are very welcome. 
Our Style: Hands-on, Practical 
Location: Online, Instructor-led 



Python Data Analytics Course

<article>
<div>
<h5>Java Machine Learning Course</h5>
</div>
<div></div>
<p>  						 
	</p><div>
	<ul>
		<p>
		<b>Python Machine Learning Course. </b>
		<br /><b>Prerequisites: </b>Basic knowledge of Python 
		<br /><b>Our Style: </b>Hands-on, Practical  
		<br /><b>Location:  </b>Online, Instructor-led  
		<br /><b>Download:  </b>anaconda.com
		<br /><b>Duration:  </b>2 consecutive days, the first of which shows as the booking date.
		<br /><b>Times: </b>10am - 5pm
	    </p>
	</ul>	

<p></p>
</div></article>

<div>
	  <div>
		 <h5>Python Machine Learning Course </h5>
	  </div>
	  <div></div>
		<p> Python Machine Learning algorithms can derive trends (learn) from data and make predictions on data by extrapolating on existing trends. Companies can take advantage of this to gain insights and ultimately improve business.
		<br />
		<br />Using Python Machine Learning scikit-learn, practice how to use Python Machine Learning algorithms to perform predictions on data.
		<br />
		<br />Learn the below listed algorithms, a small collection of available Python Machine Learning algorithms.
		<br />
		<br />Gain a good understanding of how to plan a Machine Learning project.
		We create, experiment and run example code to implement the Python Machine Learning algorithms.
	  </p>
<div>
<h5>Course Topics</h5>
</div>
<div></div>
<div>
	<ul>	  
			<li>Supervised Machine Learning:
			<strong>Classification Algorithms:</strong>  	 
					Classification Algorithms: Naive Bayes, Decision Tree, Logistic Regression, K-Nearest Neighbors, Support Vector Machine
					<br /><strong>Regression Algorithms:</strong>  Linear, Polynomial
			</li> 
	
	
			<li> <strong>  Unsupervised Machine Learning: </strong> Clustering Algorithms: K-means clustering, Hierarchical Clustering

			<br /><strong>Dimension Reduction Algorithms: </strong>Principal Component Analysis Latent Dirichlet allocation (LDA)

			<br /><strong>Association Algorithms:</strong> Apriori, Euclat

			<br /><strong>Other machine learning Algorithms:</strong>
			Reinforcement learning Algorithms: Q-Learning
			</li>
	
			<li>
			<strong>Ensemble Methods Algorithms:</strong> Stacking, bagging, boosting.
			</li> 
			
			<li>
			<strong>Random </strong>Forest Random Forest, Gradient Boosting
			</li> 
	 
		<li><strong>Neural Networks and Deep Leaning Algorithms:</strong>
		Convolutional Network (CNN)
		</li> 
		
		<li><strong>Data Exploration and Preprocessing:</strong> The first part of a Machine Learning project understands the data and the problem at hand. Data cleaning, data transformation and data pre-processing are covered using Python functions to make data exploration and preprocessing relatively easy. 
		</li>
	
		<li> Injecting domain knowledge in the process, attributes are extracted from the data and engineered into Machine Learning algorithms.
		</li> 
</ul>
</div>
		  
		
		 
</div>

Python Scikit-Learn Machine Learning Course


Prerequisites: Basic knowledge of Python 
Our Style: Hands-on, Practical 
Location: Online, Instructor-led 
Download: anaconda.com 
Duration: 1 days
Times: 11am - 5pm 
How to attend: 
You can select your dates and use the link  https://meet.goto.com/910697125  to attend
Python Machine Learning Course Description
 Python Machine Learning algorithms can derive trends (learn) from data and make predictions on data by extrapolating on existing trends. Companies can take advantage of this to gain insights and ultimately improve business. 
 
Using Python Machine Learning scikit-learn, practice how to use Python Machine Learning algorithms to perform predictions on data. 
 
Learn the below listed algorithms, a small collection of available Python Machine Learning algorithms. 
 
Gain a good understanding of how to plan a Machine Learning project. We create, experiment, and run example code to implement the Python Machine Learning algorithms. 
Course Topics
Supervised Machine Learning: Classification Algorithms: Classification Algorithms: Naive Bayes, Decision Tree, Logistic Regression, K-Nearest Neighbors, Support Vector Machine 
Regression Algorithms: Linear, Polynomial
Unsupervised Machine Learning: Clustering Algorithms: K-means clustering, Hierarchical Clustering 
Dimension Reduction Algorithms: Principal Component Analysis Latent Dirichlet allocation (LDA) 
Association Algorithms: Apriori, Euclat 
Other machine learning Algorithms: Reinforcement learning Algorithms: Q-Learning
Ensemble Methods Algorithms: Stacking, bagging, boosting.
Random Forest Random Forest, Gradient Boosting
Neural Networks and Deep Leaning Algorithms: Convolutional Network (CNN)
Data Exploration and Preprocessing: The first part of a Machine Learning project understands the data and the problem at hand. Data cleaning, data transformation and data pre-processing are covered using Python functions to make data exploration and preprocessing relatively easy.
Injecting domain knowledge in the process, attributes are extracted from the data and engineered into Machine Learning algorithms.

Unsupervised Machine Learning

Python Machine Learning algorithms can derive trends (learn) from data and make predictions on data by extrapolating on existing trends. Companies can take advantage of this to gain insights and ultimately improve business. 
 
Using Python Machine Learning scikit-learn, practice how to use Python Machine Learning algorithms to perform predictions on data. 
 
Learn the below listed algorithms, a small collection of available Python Machine Learning algorithms. 

Python Machine Learning, online instructor-led 

<div style="color: rgb(57, 54, 79); box-sizing: border-box;" id="isPasted" fr-original-style=" color: rgb(57, 54, 79);"><div data-testid="summary" id="isPasted" fr-original-style="" style="box-sizing: border-box;"><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">This Python Machine Learning online instructor led course is an excellent introduction to popular machine learning algorithms.</strong></p></div><div data-testid="organizerBrief" fr-original-style="" style="box-sizing: border-box;"><div data-testid="creator-signal-main-section" fr-original-style="" style="box-sizing: border-box;"><section fr-original-style="" style="box-sizing: border-box;"></section></div></div><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" id="isPasted" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><br fr-original-style="" style="box-sizing: border-box;"></strong></p><hr fr-original-style="" style="border-color: var(--border-muted); border-style: solid; clear: both; break-after: page; user-select: none; box-sizing: border-box;"><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" id="isPasted" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Python Machine Learning 2-day Course</strong></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><em fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Prerequisites:</strong></em></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);">Basic knowledge of Python coding is a pre-requisite.</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><em fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Who Should Attend?</strong></em></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);">This course is an overview of machine learning and machine learning algorithms in Python SciKitLearn.</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Practical:</strong></p><ul style="color: rgb(111, 114, 135); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><li fr-original-style="" style="box-sizing: border-box;">We cover the below listed algorithms, which is only a small collection of what is available. However, it will give you a good understanding, to plan your Machine Learning project</li><li fr-original-style="" style="box-sizing: border-box;">We create, experiment and run machine learning sample code to implement a short selected but representative list of available the algorithms.&nbsp;</li></ul><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Course Outline:</strong></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Supervised Machine Learning:</strong></p><ul style="color: rgb(111, 114, 135); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><li fr-original-style="" style="box-sizing: border-box;">Classification Algorithms: Naive Bayes, Decision Tree, Logistic Regression, K-Nearest Neighbors, Support Vector Machine</li><li fr-original-style="" style="box-sizing: border-box;">Regression Algorithms: Linear, Polynomial</li></ul><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Unsupervised Machine Learning:</strong></p><ul style="color: rgb(111, 114, 135); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><li fr-original-style="" style="box-sizing: border-box;">Clustering Algorithms: K-means clustering, Hierarchical Clustering</li><li fr-original-style="" style="box-sizing: border-box;">Dimension Reduction Algorithms: Principal Component Analysis Latent Dirichlet allocation (LDA)</li><li fr-original-style="" style="box-sizing: border-box;">Association Machine Learning Algorithms: Apriori, Euclat</li></ul><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Other machine learning Algorithms:</strong></p><ul style="color: rgb(111, 114, 135); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><li fr-original-style="" style="box-sizing: border-box;">Ensemble Methods ( Stacking, bagging, boosting ) Algorithms: Random Forest, Gradient Boosting</li><li fr-original-style="" style="box-sizing: border-box;">Reinforcement learning Algorithms: Q-Learning</li><li fr-original-style="" style="box-sizing: border-box;">Neural Networks and Deep Leaning Algorithms: Convolutional Network (CNN)</li></ul><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Data Exploration and Preprocessing:</strong></p><ul style="color: rgb(111, 114, 135); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><li fr-original-style="" style="box-sizing: border-box;">The first part of a Machine Learning project understands the data and the problem at hand.</li><li fr-original-style="" style="box-sizing: border-box;">Data cleaning, data transformation and data pre-processing are covered using Python functions to make data exploration and preprocessing relatively easy.</li></ul><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">What is included in this Python Machine Learning:</strong></p><ul style="color: rgb(111, 114, 135); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><li fr-original-style="" style="box-sizing: border-box;">Python Machine Learning Certificate on completion &nbsp;</li><li fr-original-style="" style="box-sizing: border-box;">Python Machine Learning notes</li><li fr-original-style="" style="box-sizing: border-box;">Practical Python Machine Learning exercises and code examples</li><li fr-original-style="" style="box-sizing: border-box;">After the course, 1 free, online session for questions or revision Python Machine Learning.</li><li fr-original-style="" style="box-sizing: border-box;">Max group size on this Python Machine Learning is 4.</li></ul></div><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><br fr-original-style="" style="box-sizing: border-box;"></p><div style="color: rgb(30, 10, 60); box-sizing: border-box;" id="isPasted" fr-original-style=" color: rgb(30, 10, 60);"><hr fr-original-style="" style="border-color: var(--border-muted); border-style: solid; clear: both; break-after: page; user-select: none; box-sizing: border-box;"><h2 fr-original-style="" style="box-sizing: border-box;">Refund Policy</h2></div><div style="color: rgb(111, 114, 135); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);">No Refunds</div>

This Python Machine Learning online instructor led course is an excellent introduction to popular machine learning algorithms.





Python Machine Learning 2-day Course
Prerequisites:
Basic knowledge of Python coding is a pre-requisite.
Who Should Attend?
This course is an overview of machine learning and machine learning algorithms in Python SciKitLearn.
Practical:
We cover the below listed algorithms, which is only a small collection of what is available. However, it will give you a good understanding, to plan your Machine Learning project
We create, experiment and run machine learning sample code to implement a short selected but representative list of available the algorithms.
Course Outline:
Supervised Machine Learning:
Classification Algorithms: Naive Bayes, Decision Tree, Logistic Regression, K-Nearest Neighbors, Support Vector Machine
Regression Algorithms: Linear, Polynomial
Unsupervised Machine Learning:
Clustering Algorithms: K-means clustering, Hierarchical Clustering
Dimension Reduction Algorithms: Principal Component Analysis Latent Dirichlet allocation (LDA)
Association Machine Learning Algorithms: Apriori, Euclat
Other machine learning Algorithms:
Ensemble Methods ( Stacking, bagging, boosting ) Algorithms: Random Forest, Gradient Boosting
Reinforcement learning Algorithms: Q-Learning
Neural Networks and Deep Leaning Algorithms: Convolutional Network (CNN)
Data Exploration and Preprocessing:
The first part of a Machine Learning project understands the data and the problem at hand.
Data cleaning, data transformation and data pre-processing are covered using Python functions to make data exploration and preprocessing relatively easy.


What is included in this Python Machine Learning:
Python Machine Learning Certificate on completion
Python Machine Learning notes
Practical Python Machine Learning exercises and code examples
After the course, 1 free, online session for questions or revision Python Machine Learning.
Max group size on this Python Machine Learning is 4.





Refund Policy
No Refunds

Python Machine Learning Course, 1-Days, Online Attendance

Python Basics 1-days Online Instructor-Led

<div style="color: rgb(57, 54, 79); box-sizing: border-box;" id="isPasted" fr-original-style=" color: rgb(57, 54, 79);"><div data-testid="summary" id="isPasted" fr-original-style="" style="box-sizing: border-box;"><div data-testid="summary" id="isPasted" fr-original-style="" style="box-sizing: border-box;"><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Python coding, interactive, instructor-led, hands-on, practical. From basics to working with professionals. Python Part Time. Python Coding.</strong></p></div><div data-testid="organizerBrief" fr-original-style="" style="box-sizing: border-box;"><div data-testid="creator-signal-main-section" fr-original-style="" style="box-sizing: border-box;"><section fr-original-style="" style="box-sizing: border-box;"><br fr-original-style="" style="box-sizing: border-box;"></section></div></div></div><hr fr-original-style="" style="border-color: var(--border-muted); border-style: solid; clear: both; break-after: page; user-select: none; box-sizing: border-box;"><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" id="isPasted" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Python Beginners Evenings Course</strong></strong></p><h2 style="color: rgb(30, 10, 60); box-sizing: border-box;" fr-original-style=" color: rgb(30, 10, 60);">Course summary</h2><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);">This Python Programming course has become essential to all professional who would like to do code using Python. Learn evenings, work while studying. Work and study Python Part Time.</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);">It is a Python beginners course and teaches Python coding from scratch to intermediate.</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);">Hands-on, practical. We code some real life examples in this course.</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><em fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Duration:</strong></strong></em><em fr-original-style="" style="box-sizing: border-box;"><em fr-original-style="" style="box-sizing: border-box;">&nbsp;3 Evenings, once per week for 3 weeks 6pm-8pm, of which the first date only shows on the booking.</em></em></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Virtual Classroom:&nbsp;</strong></strong>You could attend in our classroom, or attend online via virtual classroom, by select the appropriate ticket.</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Who Should Attend?</strong></strong></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);">This course is intended for beginner programmers who need to code in Python. Fast-paced, Quite intensive.</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Course Outline:</strong></strong></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Session&nbsp;</strong></strong><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">1: Basics</strong></strong></p><ul style="color: rgb(111, 114, 135); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Python Data Types, Variables,</strong></strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Operators and Expressions:</strong></strong>&nbsp;Arithmetic operators; Relational operators; Assignment operator; Logical operators.</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Decision Making:</strong></strong>&nbsp;If statement; If - else statement; If- elif - else statement; Nested if - else;</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Using Loops:</strong></strong>&nbsp;The while, while-else; do-while and the for loop; Enhanced for loop; Jump statements: break, continue; Nesting loops.</li></ul><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Session&nbsp;</strong></strong><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">2: Lists. Dictionaries, Json</strong></strong></p><ul style="color: rgb(111, 114, 135); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><li fr-original-style="" style="box-sizing: border-box;">Python Data Structures: Lists. Data Structures: 2-d Lists, Tuples. Dictionary, Nested Disctionary.</li></ul><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Session&nbsp;</strong></strong><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">3: Built-in functions:</strong></strong></p><ul style="color: rgb(111, 114, 135); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><li fr-original-style="" style="box-sizing: border-box;">Python Date Functions. Random. Math Functions. String Functions. Python Regex.</li></ul><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Session&nbsp;</strong></strong><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">4: Database:</strong></strong></p><ul style="color: rgb(111, 114, 135); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><li fr-original-style="" style="box-sizing: border-box;">Connect to a database, create Database, create a table, insert, delete, update records, query a database and display results. Drop database, drop table.</li></ul><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Session&nbsp;</strong></strong><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">5: Files</strong></strong></p><ul style="color: rgb(111, 114, 135); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><li fr-original-style="" style="box-sizing: border-box;">Exception Handling in Python<strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">:&nbsp;</strong></strong>Fundamentals of exception handling; Exception types; Using try and except.</li><li fr-original-style="" style="box-sizing: border-box;">Files, streams: Create<strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">,&nbsp;</strong></strong>Open, Traverse and Read Files: Csv, txt and Json Files.</li><li fr-original-style="" style="box-sizing: border-box;">API: Connecting to API&rsquo;s</li></ul><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Session&nbsp;</strong></strong><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">6</strong></strong>:&nbsp;<strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">M ethods, Classes and Objects</strong></strong></p><ul style="color: rgb(111, 114, 135); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><li fr-original-style="" style="box-sizing: border-box;">Creating and using Function, Working with parameters, Calling functions.</li><li fr-original-style="" style="box-sizing: border-box;">Object-Oriented Programming (OOP) principles. Modules and Classes, Creating an Object; Using an Object; Adding Instance variables; Controlling accessibility; Naming conventions for class member.s</li></ul><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><br fr-original-style="" style="box-sizing: border-box;"></p><div data-testid="image-content" fr-original-style="" style="box-sizing: border-box;"><img src="https://img.evbuc.com/https%3A%2F%2Fcdn.evbuc.com%2Fimages%2F447713699%2F44980801875%2F1%2Foriginal.20230216-130657?h=2000&w=720&auto=format%2Ccompress&q=75&sharp=10&s=c331eac85ab8cd495a7a46a3aa8c2b7b" alt="" data-airgap-id="86" fr-original-style="" style="cursor: pointer; padding: 0px 1px; user-select: none; max-width: 100%; position: relative; box-sizing: border-box;" fr-original-class="fr-draggable"></div><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">FAQ</strong></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Do I need Python on my Laptop?</strong></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);">Ideally spoken yes, but if not possible, you could use our online platform.</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Can I pay by BACS?</strong></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);">Yes, simply email us, a Python course consultant will contact you. training@pcworkshopslondon.co.uk or pcworkshopslondon@gmail.com</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Can I pay with PayPal?</strong></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);">Yes, simply email us, a course consultant will contact you. training@pcworkshopslondon.co.uk or pcworkshopslondon@gmail.com</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Do I get an invoice?</strong></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);">Yes, on request.</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Can I pay with a PO (Purchase Order Number)?</strong></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);">Yes, simply email us, a Python course consultant will contact you. training@pcworkshopslondon.co.uk or pcworkshopslondon@gmail.com</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Do I get a certificate?</strong></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);">Yes, a PCWorkshops Certificate</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Can I attend in classroom?</strong></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);">Yes, on request, and it would incur an additional charge, depending on your location. We have offices in London, Manchester, Birmingham, Portmouth, Southend-on-Sea, Milton Keynes.</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Can beginners follow this course?</strong></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);">Yes, this is a Python beginner friendly course. We offer Python courses with max 4 people, so we make sure each delegates fully understand the material covered</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Can I customise the course?</strong></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);">Yes, all our Python courses are customisable. We can customise the dates, times, location. course outline.</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"></p></div><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><br fr-original-style="" style="box-sizing: border-box;"></p><div style="color: rgb(30, 10, 60); box-sizing: border-box;" id="isPasted" fr-original-style=" color: rgb(30, 10, 60);"><hr fr-original-style="" style="border-color: var(--border-muted); border-style: solid; clear: both; break-after: page; user-select: none; box-sizing: border-box;"><h2 fr-original-style="" style="box-sizing: border-box;">Refund Policy</h2></div><div style="color: rgb(111, 114, 135); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);">No Refunds</div>

Python coding, interactive, instructor-led, hands-on, practical. From basics to working with professionals. Python Part Time. Python Coding.



Python Beginners Evenings Course
Course summary
This Python Programming course has become essential to all professional who would like to do code using Python. Learn evenings, work while studying. Work and study Python Part Time.
It is a Python beginners course and teaches Python coding from scratch to intermediate.
Hands-on, practical. We code some real life examples in this course.
Duration: 4 Evenings, once per week for 34weeks 6pm-8pm, of which the first date only shows on the booking.
Virtual Classroom: You could attend in our classroom, or attend online via virtual classroom, by select the appropriate ticket.
Who Should Attend?
This course is intended for beginner programmers who need to code in Python. Fast-paced, Quite intensive.
Course Outline:
Session 1: Basics
Python Data Types, Variables,
Operators and Expressions: Arithmetic operators; Relational operators; Assignment operator; Logical operators.
Decision Making: If statement; If - else statement; If- elif - else statement; Nested if - else;
Using Loops: The while, while-else; do-while and the for loop; Enhanced for loop; Jump statements: break, continue; Nesting loops.
Session 2: Lists. Dictionaries, Json
Python Data Structures: Lists. Data Structures: 2-d Lists, Tuples. Dictionary, Nested Disctionary. API's. Exceptions and CSV Files
Session 3: Built-in functions:
Python Random. Math Functions. String Functions.
Database:
Connect to a database, query a database and display results. 
Session 4: Methods, Classes and Objects
Creating and using Function, Working with parameters, Calling functions.
Object-Oriented Programming (OOP) principles. Modules and Classes, Creating an Object; Using an Object; Adding Instance variables; Controlling accessibility; Naming conventions for class member.s



FAQ
Do I need Python on my Laptop?
Ideally spoken yes, but if not possible, you could use our online platform.
Can I pay by BACS?
Yes, simply email us, a Python course consultant will contact you. training@pcworkshopslondon.co.uk or pcworkshopslondon@gmail.com
Can I pay with PayPal?
Yes, simply email us, a course consultant will contact you. training@pcworkshopslondon.co.uk or pcworkshopslondon@gmail.com
Do I get an invoice?
Yes, on request.
Can I pay with a PO (Purchase Order Number)?
Yes, simply email us, a Python course consultant will contact you. training@pcworkshopslondon.co.uk or pcworkshopslondon@gmail.com
Do I get a certificate?
Yes, a PCWorkshops Certificate
Can I attend in classroom?
Yes, on request, and it would incur an additional charge, depending on your location. We have offices in London, Manchester, Birmingham, Portmouth, Southend-on-Sea, Milton Keynes.
Can beginners follow this course?
Yes, this is a Python beginner friendly course. We offer Python courses with max 4 people, so we make sure each delegates fully understand the material covered
Can I customise the course?
Yes, all our Python courses are customisable. We can customise the dates, times, location. course outline.






Refund Policy
No Refunds

Course summary



This Python Programming course has become essential to all professional who would like to do code using Python. Learn evenings, work while studying. Work and study Python Part Time.



It is a Python beginners course and teaches Python coding from scratch to intermediate.



Hands-on, practical. We code some real life examples in this course.



Python Programming Beginners Evenings Course, Virtual Classroom.

Keep 020 7164 6359 for your contact on the day. Thanks for booking!

Python Evenings in Classroom, London

<p><strong> Boost Your Career By Enrolling On This Python Course To Get Through Challenging Moments!</strong></p><p><em><strong>Become a Python programmer and study one of the most in-demand talents for employers in the upcoming year!</strong></em></p><p>This is the most extensive, but simple, Python programming language course available! This programming language course is for you whether you've never coded before, know basic grammar, or want to learn about Python's advanced techniques. You will learn the Python programming language course the way that suits you best!</p><p>This course is accredited by <strong>CPD </strong>with <strong>10 CPD points</strong> for professional development. Students can expect to complete this course in around <strong>09 hours</strong>. You'll also get dedicated expert assistance from us to answer any queries you may have while studying our course.</p><p>Upon successful completion of the Python course, an instant e-certificate will be exhibited in your profile that you can order as proof of your new skills and knowledge. Add these amazing new skills to your resume and boost your employability by simply enrolling in this course.</p><p>You'll get a <strong>Free Student ID</strong> card by enrolling in this course. This ID card entitles you to discounts on bus tickets, movie tickets, and library cards.</p><p>This course can help you to accomplish your ambitions and prepare you for a meaningful career. So, join the course today - gear up with the essential skills to set yourself up for excellence!</p><p><strong>What you will learn from this Course?</strong></p><ul><li>Become a skilled Developer</li><li>How to use the basic structures: strings, lists, and dictionaries</li><li>How to use Object-Oriented Programming (OOP)</li><li>How to use core programming tools such as functions and loops</li><li>How to land your first job as a Developer</li><li>write Python scripts to perform automated actions</li><li>Start creating your Python programs from scratch</li><li>Learn to use variables to store, retrieve and calculate information</li></ul><p><strong>Why should you choose this course with Academy for Health &amp; Fitness?</strong></p><ul><li>Opportunity to earn a certificate accredited by <strong>CPD </strong>after completing this course</li><li><strong>Student ID</strong> card with amazing discounts - completely for <strong> FREE!</strong> (£10 postal charges will be applicable for international delivery)</li><li>Globally accepted standard structured lesson planning</li><li>Innovative and engaging content and activities</li><li>Assessments that measure higher-level thinking and skills</li><li>Complete the program in your own time, at your own pace</li><li>Each of our students gets full 24/7 tutor support</li></ul> <p>With this comprehensive course, you can achieve your dreams and train for your ideal career. The Python course provides students with an in-depth learning experience that they can work through at their own pace to enhance their professional development.</p><p>Start your learning journey straight away with this course and take a step toward a brighter future!</p><p><strong>*** Course Curriculum ***</strong></p><p><strong></strong><strong> Learn Programming with Python Course</strong><strong></strong></p><p><strong>Module 01:</strong></p><ul><li>An Installing Python</li><li>Documentation</li><li>Command-Line</li><li>Variables</li><li>Simple Python Syntax</li><li>Keywords</li><li>Import-Module</li></ul><p><strong>Module 02:</strong></p><ul><li>Additional Topics</li><li>If Elif Else</li><li>Iterable</li><li>For</li><li>Loops in Python</li><li>Execute</li><li>Exceptions</li></ul><p><strong>Module 03:</strong></p><ul><li>Data Types</li><li>Number Types</li><li>More Number Types</li><li>Strings</li><li>More Strings</li><li>Files</li><li>Lists</li><li>Dictionaries</li><li>Tuples</li><li>Sets</li></ul><p><strong>Module 04:</strong></p><ul><li>Comprehensions</li><li>Definitions</li><li>Functions</li><li>Default Arguments</li><li>Doc Strings</li><li>Variadic Functions</li><li>Factorial</li></ul><p><strong>Module 05:</strong></p><ul><li>Function Objects</li><li>Lambda</li><li>Generators</li><li>Object Initialization</li><li>Class Static Members</li><li>Classic Inheritance</li><li>Data Hiding</li></ul><p><strong>Assessment Process</strong></p><p>Once you have completed all the modules in the Python course, your skills and knowledge will be tested with an automated multiple-choice assessment. You will then receive instant results to let you know if you have successfully passed the course.</p><p><strong>Show off Your New Skills with a Certificate of Completion</strong></p><p>The learners have to successfully complete the assessment of this Course to achieve the <strong>CPD accredited certificate.</strong> Digital certificates can be ordered for only £10. The learner can purchase printed hard copies inside the UK for £29, and international students can purchase printed hard copies for £39.</p> <h2>
        
        <div>CPD</div>
    </h2>

                        <div id="cpd">
                            <div>
                                <div>
                                    <div>
                                        10 CPD hours / points
                                    </div>
                                        <div>
                                            Accredited by CPD Quality Standards
                                        </div>
                                </div>
                            </div>
                        </div> <h2>
        
        <div>Who is this course for?</div>
    </h2>

                        <div id="who_is_this_course_for">
                            <p>Anyone interested in learning more about the topic is advised to take this course. This course is open to everybody.</p>
                        </div> <h2>
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                            <p>You will not need any prior background or expertise to enrol in this course.</p>
                        </div> <h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                            <p>After completing this course, you are to start your career or begin the next phase of your career.</p>
                        </div> <h2>
        
        <div>Certificates</div>
    </h2>

                        <div id="optional_extras">
                                    <h4>Certificate of completion</h4>
        <p>
            Digital certificate -
            £10
        </p>
        <h4>CPD Accredited Certificate </h4>
        <p>
            Hard copy certificate -
            £29
        </p>
            <div> <p>If you are an international student, then you have to pay an additional 10 GBP as an international delivery charge.</p> </div>

                        </div>

Boost Your Career By Enrolling On This Python Course To Get Through Challenging Moments!
Become a Python programmer and study one of the most in-demand talents for employers in the upcoming year!
This is the most extensive, but simple, Python programming language course available! This programming language course is for you whether you've never coded before, know basic grammar, or want to learn about Python's advanced techniques. You will learn the Python programming language course the way that suits you best!
This course is accredited by CPD with 10 CPD points for professional development. Students can expect to complete this course in around 09 hours. You'll also get dedicated expert assistance from us to answer any queries you may have while studying our course.
Upon successful completion of the Python course, an instant e-certificate will be exhibited in your profile that you can order as proof of your new skills and knowledge. Add these amazing new skills to your resume and boost your employability by simply enrolling in this course.
You'll get a Free Student ID card by enrolling in this course. This ID card entitles you to discounts on bus tickets, movie tickets, and library cards.
This course can help you to accomplish your ambitions and prepare you for a meaningful career. So, join the course today - gear up with the essential skills to set yourself up for excellence!
What you will learn from this Python Course?
Become a skilled Developer
How to use the basic structures: strings, lists, and dictionaries
How to use Object-Oriented Programming (OOP)
How to use core programming tools such as functions and loops
How to land your first job as a Developer
write Python scripts to perform automated actions
Start creating your Python programs from scratch
Learn to use variables to store, retrieve and calculate information
Why should you choose this course with Academy for Health & Fitness?
Opportunity to earn a certificate accredited by CPD after completing this course
Student ID card with amazing discounts - completely for FREE! (£10 postal charges will be applicable for international delivery)
Globally accepted standard structured lesson planning
Innovative and engaging content and activities
Assessments that measure higher-level thinking and skills
Complete the program in your own time, at your own pace
Each of our students gets full 24/7 tutor support
With this comprehensive course, you can achieve your dreams and train for your ideal career. The Python course provides students with an in-depth learning experience that they can work through at their own pace to enhance their professional development.



Start your learning journey straight away with this Python course and take a step toward a brighter future!
*** Course Curriculum ***
Learn Programming with Python Course
Module 01:
An Installing Python
Documentation
Command-Line
Variables
Simple Python Syntax
Keywords
Import-Module
Module 02:
Additional Topics
If Elif Else
Iterable
For
Loops in Python
Execute
Exceptions
Module 03:
Data Types
Number Types
More Number Types
Strings
More Strings
Files
Lists
Dictionaries
Tuples
Sets
Module 04:
Comprehensions
Definitions
Functions
Default Arguments
Doc Strings
Variadic Functions
Factorial
Module 05:
Function Objects
Lambda
Generators
Object Initialization
Class Static Members
Classic Inheritance
Data Hiding
Assessment Process
Once you have completed all the modules in the Python course, your skills and knowledge will be tested with an automated multiple-choice assessment. You will then receive instant results to let you know if you have successfully passed the course.
Show off Your New Skills with a Certificate of Completion
The learners have to successfully complete the assessment of this Course to achieve the CPD accredited certificate. Digital certificates can be ordered for only £10. The learner can purchase printed hard copies inside the UK for £29, and international students can purchase printed hard copies for £39.
CPD 
10 CPD hours / points  Accredited by CPD Quality Standards



Who is this course for? 
Anyone interested in learning more about the topic is advised to take this Python course. This course is open to everybody.



Requirements 
You will not need any prior background or expertise to enrol in this Python course.



Career path
After completing this Python course, you are to start your career or begin the next phase of your career.



Certificates 
Certificate of completion
Digital certificate - £10 
CPD Accredited Certificate
Hard copy certificate - £29 
If you are an international student, then you have to pay an additional 10 GBP as an international delivery charge.

Academy for Health and Fitness

Assessment Practising Certificate (APC)

Continuous Professional Development (CPD)

Python - CPD Accredited

<article>
<div>
<h5>Java Course 1 hour. Code the Hangman</h5>
</div>
<div></div>
<p>  						 
	</p><div>
	<ul>
		<p>
		<b>Python Course, code the Hangman. </b>Basic Python Course covers in one hour the coding of an interesting app. 
		<br />Any one very welcome.  
		<br /><b>Our Style: </b>Hands-on, Practical  
		<br /><b>Location:  </b>Online, Instructor-led  
		<br /><b>Download:  </b>anaconda.com
		<br /><b>Duration:  </b>1 Hour
		<br /><b>Times: </b>arrange a time for your time zone
	    </p>
	</ul>	

<p></p>
</div></article>

<div>
	  <div>
		 <h5>Python Basics Course Description</h5>
	  </div>
	  <div></div>
	  <p> Learn to code the Hangman Game in 1 hour. 
		<br /> Essentials of Python programming, explaining Python technology. 
		<br /> Practical Python lessons and Python exercises. 
		<br /> Great Tutors. 
		<br /> Online. 
		<br /> Learn plenty in one day: Code The Hangman Game in Python
	  </p>
	<div>
	<h5>Code the Hangman Game</h5>
	</div>
	<div></div>
	<div> 
		<p>  <strong>Python Course 1 Hour:</strong>  
		<br />  	STEP 1: Using variables. Arithmetic operations. Strings. String Functions
		<br />  	STEP 2: Getting user input from console. Decision Making (If-else).
		<br />  	STEP 3: For and While Loops. Repeat code by using loops.
		<br />  	STEP 4: Lists: Create, Update, Iterate Lists. Using indexes to refer to individual values.
		<br />  	STEP 5: Object Oriented Programming: Functions. Classes.  
		<br />  	STEP 6: Create the Hangman Game.			
		</p>
	</div>
 
</div>
 

<div>   

	   <div id="cincluded">
		  <div>
			 <h5>What is included with The Python Course 1 Hour</h5>
		  </div>

		  <article>
		  <div>
			 <ul>
				<li>PCWorkshops Python Course Certificate on completion  </li> 
				<li>Python Course Notes</li>
				<li>Python Code Examples</li>
				<li>Practical Python Course exercises and Code Samples</li>
				<li>After the course: 1-Hour personalised online revision session</li>
			 </ul>
		  </div>
		  </article>
	   </div>
				    
<div>
	                  <div>
	                     <h5 id="cincluded2">Book the Python Course 1 hour</h5>
	                  </div>
 
	 
 <div id="eventbrite-widget-container-69413456517"></div>




									
					
					 
</div>
				   <div id="caboutus">
	                  <div>
	                     <h5>About us</h5>
	                  </div> 
	                  	<article>
					    <div>
					    	<div>
					    		<div>
					    			
					    			<h5>Our experienced trainers are award winners. </h5> 
					    			<ul>
										<li>
											More about us
										</li>
										<li>
											FAQ's
										</li>
										<li>
											Client Comments  
										</li>
									 </ul>
					    		</div>
					    		<div>
					    			
					    				
					    			
					    		</div>
					    	</div>
	                     
					    </div>
					    </article>						
	               </div>
				   
				   
	        </div>

Java Course 1 hour. Code the Hangman
Online, Instructor-led
 
 Python Course, code the Hangman. Basic Python Course covers in one hour the coding of an interesting app. 
Any one very welcome. 
Our Style: Hands-on, Practical 

Location: Online, Instructor-led 
Download: anaconda.com 
Duration: 1 Hour 
Times: arrange a time for your time zone 
Python Basics Course Description
 Learn to code the Hangman Game in 1 hour. 
 Essentials of Python programming, explaining Python technology. 
 Practical Python lessons and Python exercises. 
 Great Tutors. 
 Online. 
 Learn plenty in one day: Code The Hangman Game in Python 
Code the Hangman Game
 Python Course 1 Hour: 
 STEP 1: Using variables. Arithmetic operations. Strings. String Functions 
 STEP 2: Getting user input from console. Decision Making (If-else). 
 STEP 3: For and While Loops. Repeat code by using loops. 
 STEP 4: Lists: Create, Update, Iterate Lists. Using indexes to refer to individual values. 
 STEP 5: Object Oriented Programming: Functions. Classes. 
 STEP 6: Create the Hangman Game. 
What is included with The Python Course 1 Hour
PCWorkshops Python Course Certificate on completion
Python Course Notes
Python Code Examples
Practical Python Course exercises and Code Samples
After the course: 1-Hour personalised online revision session
Book the Python Course 1 hour
About us
Our experienced trainers are award winners.
More about us
FAQ's
Client Comments

Application Software

Computing & Software Development Tools

Coding For Kids

Remote Desktop Software

Software Development

Python Course, code the Hangman. Basic Python Course covers in one hour the coding of an interesting app. 
Any one very welcome. 
Our Style: Hands-on, Practical 
Location: Online, Instructor-led 
Download: anaconda.com 
Duration: 1 Hour 
Times: arrange a time for your time zone 

Python Taster, Code the Hangman, Online Instrcutor-led 

<div style="color: rgb(57, 54, 79); box-sizing: border-box;" id="isPasted" fr-original-style=" color: rgb(57, 54, 79);"><div data-testid="summary" id="isPasted" fr-original-style="" style="box-sizing: border-box;"><div data-testid="summary" id="isPasted" fr-original-style="" style="box-sizing: border-box;"><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Powerful 1-hour Python workshop course understand Python Basics. Practical. Instructor-led. Online.</strong></p></div><div data-testid="organizerBrief" fr-original-style="" style="box-sizing: border-box;"><div data-testid="creator-signal-main-section" fr-original-style="" style="box-sizing: border-box;"><section fr-original-style="" style="box-sizing: border-box;"><br fr-original-style="" style="box-sizing: border-box;"></section></div></div></div><hr fr-original-style="" style="border-color: var(--border-muted); border-style: solid; clear: both; break-after: page; user-select: none; box-sizing: border-box;"><h1 style="color: rgb(57, 54, 79); box-sizing: border-box;" id="isPasted" fr-original-style=" color: rgb(57, 54, 79);">Learn to code a Password Validator in 1 hour.&nbsp;</h1><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);">Basics made simple! &nbsp;Learn plenty in one day: Code A Password Validator</p><ul style="color: rgb(111, 114, 135); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><li fr-original-style="" style="box-sizing: border-box;">Essentials of Python programming.</li><li fr-original-style="" style="box-sizing: border-box;">Practical lessons and exercises.</li><li fr-original-style="" style="box-sizing: border-box;">Great Tutors.&nbsp;</li><li fr-original-style="" style="box-sizing: border-box;">Online.</li><li fr-original-style="" style="box-sizing: border-box;">You may Request a Central London Location, per email</li></ul><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Who will the Course Benefit?</strong></p><ul style="color: rgb(111, 114, 135); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><li fr-original-style="" style="box-sizing: border-box;">This is a fantastic course for beginners</li><li fr-original-style="" style="box-sizing: border-box;">Or for coders, simply fast-track crossing over to Python.</li></ul><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Teaching Style:&nbsp;</strong>Practical, Interactive, Personalised. Useful examples.</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">What is included?</strong></p><ul style="color: rgb(111, 114, 135); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><li fr-original-style="" style="box-sizing: border-box;">Course notes, exercises and examples.</li><li fr-original-style="" style="box-sizing: border-box;">Course certificate.</li></ul><h2 style="color: rgb(30, 10, 60); box-sizing: border-box;" fr-original-style=" color: rgb(30, 10, 60);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Learn Python by coding a Password Validator</strong></h2><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">STEP 1:&nbsp;</strong>Using variables. Arithmetic operations. Strings. String Functions</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">STEP 2:&nbsp;</strong>Getting user input from console. Decision Making(If-else)</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">STEP 3:&nbsp;</strong>For and While Loops. Repeat code by using loops.</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">STEP 4:&nbsp;</strong>Lists: Create, Update, Iterate Lists. Using indexes to refer to individual values.</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">STEP 5:&nbsp;</strong>Object Oriented Programming. Functions. Classes.</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">STEP 6:&nbsp;</strong>Create the Password Validator</p></div><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><br fr-original-style="" style="box-sizing: border-box;"></p><div style="color: rgb(30, 10, 60); box-sizing: border-box;" id="isPasted" fr-original-style=" color: rgb(30, 10, 60);"><hr fr-original-style="" style="border-color: var(--border-muted); border-style: solid; clear: both; break-after: page; user-select: none; box-sizing: border-box;"><h2 fr-original-style="" style="box-sizing: border-box;">Refund Policy</h2></div><div style="color: rgb(111, 114, 135); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);">No Refunds</div>

Powerful 1-hour Python workshop course understand Python Basics. Practical. Instructor-led. Online.



Learn to code a Password Validator in 1 hour. 
Basics made simple! Learn plenty in one day: Code A Password Validator
Essentials of Python programming.
Practical lessons and exercises.
Great Tutors.
Online.
You may Request a Central London Location, per email
Who will the Course Benefit?
This is a fantastic course for beginners
Or for coders, simply fast-track crossing over to Python.
Teaching Style: Practical, Interactive, Personalised. Useful examples.
What is included?
Course notes, exercises and examples.
Course certificate.
Learn Python by coding a Password Validator
STEP 1: Using variables. Arithmetic operations. Strings. String Functions
STEP 2: Getting user input from console. Decision Making(If-else)
STEP 3: For and While Loops. Repeat code by using loops.
STEP 4: Lists: Create, Update, Iterate Lists. Using indexes to refer to individual values.
STEP 5: Object Oriented Programming. Functions. Classes.
STEP 6: Create the Password Validator





Refund Policy
No Refunds

Powerful 1-hour Python workshop course understand Python Basics. Practical. Instructor-led. Online.
Learn to code a Password Validator in 1 hour. 



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