Name: Making Automated Trading Bot Using Python
Price: 10.99 GBP
Availability: InStock

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			<h2>Overview
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					<p><span>This comprehensive course on </span><b><span>Data Science &amp; Machine Learning with Python</span></b> will deepen your understanding on this topic.</p><p><span><span>After successful completion of this course you can acquire the required skills in this sector. This </span><b>Data Science &amp; Machine Learning with Python</b> comes with accredited certification from CPD, which will enhance your CV and make you worthy in the job market.</span></p><p><span><span>So enrol in this course today to fast track your career ladder.</span></span></p>					</div>
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			<h2>How will I get my certificate?</h2>		</div>
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					<p>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.<br /></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 </span><b><span>Data Science &amp; Machine Learning with Python</span></b>. It is available to all students, of all academic backgrounds.</p>					</div>
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			<h2>Requirements</h2>		</div>
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					<p><span>Our </span><b><span>Data Science &amp; Machine Learning with Python</span></b> 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.</p><p><span><span>There is no time limit for completing this course, it can be studied in your own time at your own pace.</span></span></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>2 sections • 90 lectures • 10:24:00 total length</p></div><div><div><div><div><div><div><div><p>•Course Overview &amp; Table of Contents: 00:09:00</p></div><div><div><p>•Introduction to Machine Learning - Part 1 - Concepts , Definitions and Types: 00:05:00</p></div><div><div><p>•Introduction to Machine Learning - Part 2 - Classifications and Applications: 00:06:00</p></div><div><div><p>•System and Environment preparation - Part 1: 00:08:00</p></div><div><div><p>•System and Environment preparation - Part 2: 00:06:00</p></div><div><div><p>•Learn Basics of python - Assignment 1: 00:10:00</p></div><div><div><p>•Learn Basics of python - Assignment 2: 00:09:00</p></div><div><div><p>•Learn Basics of python - Functions: 00:04:00</p></div><div><div><p>•Learn Basics of python - Data Structures: 00:12:00</p></div><div><div><p>•Learn Basics of NumPy - NumPy Array: 00:06:00</p></div><div><div><p>•Learn Basics of NumPy - NumPy Data: 00:08:00</p></div><div><div><p>•Learn Basics of NumPy - NumPy Arithmetic: 00:04:00</p></div><div><div><p>•Learn Basics of Matplotlib: 00:07:00</p></div><div><div><p>•Learn Basics of Pandas - Part 1: 00:06:00</p></div><div><div><p>•Learn Basics of Pandas - Part 2: 00:07:00</p></div><div><div><p>•Understanding the CSV data file: 00:09:00</p></div><div><div><p>•Load and Read CSV data file using Python Standard Library: 00:09:00</p></div><div><div><p>•Load and Read CSV data file using NumPy: 00:04:00</p></div><div><div><p>•Load and Read CSV data file using Pandas: 00:05:00</p></div><div><div><p>•Dataset Summary - Peek, Dimensions and Data Types: 00:09:00</p></div><div><div><p>•Dataset Summary - Class Distribution and Data Summary: 00:09:00</p></div><div><div><p>•Dataset Summary - Explaining Correlation: 00:11:00</p></div><div><div><p>•Dataset Summary - Explaining Skewness - Gaussian and Normal Curve: 00:07:00</p></div><div><div><p>•Dataset Visualization - Using Histograms: 00:07:00</p></div><div><div><p>•Dataset Visualization - Using Density Plots: 00:06:00</p></div><div><div><p>•Dataset Visualization - Box and Whisker Plots: 00:05:00</p></div><div><div><p>•Multivariate Dataset Visualization - Correlation Plots: 00:08:00</p></div><div><div><p>•Multivariate Dataset Visualization - Scatter Plots: 00:05:00</p></div><div><div><p>•Data Preparation (Pre-Processing) - Introduction: 00:09:00</p></div><div><div><p>•Data Preparation - Re-scaling Data - Part 1: 00:09:00</p></div><div><div><p>•Data Preparation - Re-scaling Data - Part 2: 00:09:00</p></div><div><div><p>•Data Preparation - Standardizing Data - Part 1: 00:07:00</p></div><div><div><p>•Data Preparation - Standardizing Data - Part 2: 00:04:00</p></div><div><div><p>•Data Preparation - Normalizing Data: 00:08:00</p></div><div><div><p>•Data Preparation - Binarizing Data: 00:06:00</p></div><div><div><p>•Feature Selection - Introduction: 00:07:00</p></div><div><div><p>•Feature Selection - Uni-variate Part 1 - Chi-Squared Test: 00:09:00</p></div><div><div><p>•Feature Selection - Uni-variate Part 2 - Chi-Squared Test: 00:10:00</p></div><div><div><p>•Feature Selection - Recursive Feature Elimination: 00:11:00</p></div><div><div><p>•Feature Selection - Principal Component Analysis (PCA): 00:09:00</p></div><div><div><p>•Feature Selection - Feature Importance: 00:07:00</p></div><div><div><p>•Refresher Session - The Mechanism of Re-sampling, Training and Testing: 00:12:00</p></div><div><div><p>•Algorithm Evaluation Techniques - Introduction: 00:07:00</p></div><div><div><p>•Algorithm Evaluation Techniques - Train and Test Set: 00:11:00</p></div><div><div><p>•Algorithm Evaluation Techniques - K-Fold Cross Validation: 00:09:00</p></div><div><div><p>•Algorithm Evaluation Techniques - Leave One Out Cross Validation: 00:05:00</p></div><div><div><p>•Algorithm Evaluation Techniques - Repeated Random Test-Train Splits: 00:07:00</p></div><div><div><p>•Algorithm Evaluation Metrics - Introduction: 00:09:00</p></div><div><div><p>•Algorithm Evaluation Metrics - Classification Accuracy: 00:08:00</p></div><div><div><p>•Algorithm Evaluation Metrics - Log Loss: 00:03:00</p></div><div><div><p>•Algorithm Evaluation Metrics - Area Under ROC Curve: 00:06:00</p></div><div><div><p>•Algorithm Evaluation Metrics - Confusion Matrix: 00:10:00</p></div><div><div><p>•Algorithm Evaluation Metrics - Classification Report: 00:04:00</p></div><div><div><p>•Algorithm Evaluation Metrics - Mean Absolute Error - Dataset Introduction: 00:06:00</p></div><div><div><p>•Algorithm Evaluation Metrics - Mean Absolute Error: 00:07:00</p></div><div><div><p>•Algorithm Evaluation Metrics - Mean Square Error: 00:03:00</p></div><div><div><p>•Algorithm Evaluation Metrics - R Squared: 00:04:00</p></div><div><div><p>•Classification Algorithm Spot Check - Logistic Regression: 00:12:00</p></div><div><div><p>•Classification Algorithm Spot Check - Linear Discriminant Analysis: 00:04:00</p></div><div><div><p>•Classification Algorithm Spot Check - K-Nearest Neighbors: 00:05:00</p></div><div><div><p>•Classification Algorithm Spot Check - Naive Bayes: 00:04:00</p></div><div><div><p>•Classification Algorithm Spot Check - CART: 00:04:00</p></div><div><div><p>•Classification Algorithm Spot Check - Support Vector Machines: 00:05:00</p></div><div><div><p>•Regression Algorithm Spot Check - Linear Regression: 00:08:00</p></div><div><div><p>•Regression Algorithm Spot Check - Ridge Regression: 00:03:00</p></div><div><div><p>•Regression Algorithm Spot Check - Lasso Linear Regression: 00:03:00</p></div><div><div><p>•Regression Algorithm Spot Check - Elastic Net Regression: 00:02:00</p></div><div><div><p>•Regression Algorithm Spot Check - K-Nearest Neighbors: 00:06:00</p></div><div><div><p>•Regression Algorithm Spot Check - CART: 00:04:00</p></div><div><div><p>•Regression Algorithm Spot Check - Support Vector Machines (SVM): 00:04:00</p></div><div><div><p>•Compare Algorithms - Part 1 : Choosing the best Machine Learning Model: 00:09:00</p></div><div><div><p>•Compare Algorithms - Part 2 : Choosing the best Machine Learning Model: 00:05:00</p></div><div><div><p>•Pipelines : Data Preparation and Data Modelling: 00:11:00</p></div><div><div><p>•Pipelines : Feature Selection and Data Modelling: 00:10:00</p></div><div><div><p>•Performance Improvement: Ensembles - Voting: 00:07:00</p></div><div><div><p>•Performance Improvement: Ensembles - Bagging: 00:08:00</p></div><div><div><p>•Performance Improvement: Ensembles - Boosting: 00:05:00</p></div><div><div><p>•Performance Improvement: Parameter Tuning using Grid Search: 00:08:00</p></div><div><div><p>•Performance Improvement: Parameter Tuning using Random Search: 00:06:00</p></div><div><div><p>•Export, Save and Load Machine Learning Models : Pickle: 00:10:00</p></div><div><div><p>•Export, Save and Load Machine Learning Models : Joblib: 00:06:00</p></div><div><div><p>•Finalizing a Model - Introduction and Steps: 00:07:00</p></div><div><div><p>•Finalizing a Classification Model - The Pima Indian Diabetes Dataset: 00:07:00</p></div><div><div><p>•Quick Session: Imbalanced Data Set - Issue Overview and Steps: 00:09:00</p></div><div><div><p>•Iris Dataset : Finalizing Multi-Class Dataset: 00:09:00</p></div><div><div><p>•Finalizing a Regression Model - The Boston Housing Price Dataset: 00:08:00</p></div><div><div><p>•Real-time Predictions: Using the Pima Indian Diabetes Classification Model: 00:07:00</p></div><div><div><p>•Real-time Predictions: Using Iris Flowers Multi-Class Classification Dataset: 00:03:00</p></div><div><div><p>•Real-time Predictions: Using the Boston Housing Regression Model: 00:08:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Resources - Data Science &amp; Machine Learning with Python: 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></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

Learning & Development

Computing Skills

Data Science

Data Skills

Trainers Course

Data Science & Machine Learning with Python

General Admission

<div id="course-pills-1">Duration<p>3 Days</p><p>18 CPD hours</p>This course is intended for<p>This course is aimed at anyone who wants to harness the power of data analytics in their organization including:<br />Business Analysts, Data Analysts, Reporting and BI professionals<br />Analytics professionals and Data Scientists who would like to learn Python</p>Overview<p>This course teaches delegates with no prior programming or data analytics experience how to perform data manipulation, data analysis and data visualization in Python. Mastery of these techniques and how to apply them to business problems will allow delegates to immediately add value in their workplace by extracting valuable insight from company data to allow better, data-driven decisions.<br />Outcome: After attending this course, delegates will: <br />Be able to write effective Python code <br />Know how to access their data from a variety of sources using Python<br />Know how to identify and fix data quality using Python<br />Know how to manipulate data to create analysis ready data<br />Know how to analyze and visualize data to drive data driven decisioning across your organization</p><p>Becoming a world class data analytics practitioner requires mastery of the most sophisticated data analytics tools. These programming languages are some of the most powerful and flexible tools in the data analytics toolkit.</p></div><div id="course-pills-2"><h4>From business questions to data analytics, and beyond</h4><ul><li>For data analytics tasks to affect business decisions they must be driven by a business question.  This section will formally outline how to move an analytics project through key phases of development from business question to business solution.  Delegates will be able:</li><li>to describe and understand the general analytics process. </li><li>to describe and understand the different types of analytics can be used to derive data driven solutions to business </li><li>to apply that knowledge to their business context</li></ul><h4>Basic Python Programming Conventions</h4><ul><li>This section will cover the basics of writing R programs. Topics covered will include:</li><li>What is Python?</li><li>Using Anaconda</li><li>Writing Python programs</li><li>Expressions and objects</li><li>Functions and arguments</li><li>Basic Python programming conventions</li></ul><h4>Data Structures in Python</h4><ul><li>This section will look at the basic data structures that Python uses and accessing data in Python. Topics covered will include:</li><li>Vectors</li><li>Arrays and matrices </li><li>Factors</li><li>Lists</li><li>Data frames</li><li>Loading .csv files into Python</li></ul><h4>Connecting to External Data</h4><ul><li>This section will look at loading data from other sources into Python. Topics covered will include:</li><li>Loading .csv files into a pandas data frame</li><li>Connecting to and loading data from a database into a panda data frame</li></ul><h4>Data Manipulation in Python</h4><ul><li>This section will look at how Python can be used to perform data manipulation operations to prepare datasets for analytics projects. Topics covered will include:</li><li>Filtering data</li><li>Deriving new fields</li><li>Aggregating data</li><li>Joining data sources</li><li>Connecting to external data sources</li></ul><h4>Descriptive Analytics and Basic Reporting in Python</h4><ul><li>This section will explain how Python can be used to perform basic descriptive. Topics covered will include:</li><li>Summary statistics</li><li>Grouped summary statistics</li><li>Using descriptive analytics to assess data quality</li><li>Using descriptive analytics to created business report</li><li>Using descriptive analytics to conduct exploratory analysis</li></ul><h4>Statistical Analysis in Python</h4><ul><li>This section will explain how Python can be used to created more interesting statistical analysis. Topics covered will include:</li><li>Significance tests</li><li>Correlation</li><li>Linear regressions</li><li>Using statistical output to create better business decisions.</li></ul><h4>Data Visualisation in Python</h4><ul><li>This section will explain how Python can be used to create effective charts and visualizations. Topics covered will include:</li><li>Creating different chart types such as bar charts, box plots, histograms and line plots</li><li>Formatting charts</li></ul><h4>Best Practices Hints and Tips</h4><ul><li>This section will go through some best practice considerations that should be adopted of you are applying Python in a business context.</li><li></li></ul></div>

Nexus Human

Business Analytics & Intelligence

Excel Analytics

Big Data Analytics

Data Analyst

Python for Data Analytics

Redhill

<h3><b>Network automation training course description</b></h3> 
				<p> This course concentrates on the technical side of tools
and languages for network DevOps rather than the soft
skills. These tools include Python, Ansible, Git and
NAPALM
By the end of the course delegates should be able to
recognise the tools that they can use to automate their
networks and be able to use the knowledge gained to
feel confident approaching network automation.</p>
        
				<h5><b>What will you learn</b></h5>
				<ul>
				 
          <li>Describe network DevOps.</li>
					<li>Choose network automation tools.</li>
                    <li>Explain the role of various network automation
technologies including:<br />

                    Python<br />
                   Ansible<br />
                    Git<br />
											NAPALM</li>
                    </ul>
       
        <h5>
        <b>Network automation training course details</b> </h5>
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					<div>
						<ul>
							<li><b> Who will benefit:</b> </li>
							
              <p>Those wishing to learn about the tools of network
automation.</p>
              
							<li><b>Prerequisites:</b></li>
							
              <p>Introduction to data communications.</p>
              
							<li><b>Duration</b></li>
							
              <p>1 day
						</p>
              
							
              
              
						</ul>
					</div>
				</div>
      <h3><b>Network automation training course contents</b></h3>
      <ul>
				<li>What is DevOps and network automation</li><p>
Programming and automating networks, networks
and clouds, AWS, OpenStack, SDN, DevOps for
network operations. Unit testing. Hype vs reality.
Benefits and features.
				</p><li>Network monitoring and troubleshooting</li><p>
Traditional methods, SNMP. Netflow and xflow.
Traditional automation. Streaming telemetry.
Event driven automation. gRPC, Protocol buffers.
</p><li>Configuration management</li><p>
Catch 22 and initial configuration. ZTP, POAP.
Traditional automation. TFTP. Ansible vs the rest
(chef, salt, puppet). Jinja2 and templating. How
ansible works.
</p><li>Network programmability</li><p>
Programming languages. Linux, shell scripting.
Python vs the rest. Off box vs on box automation.
</p><li>Python network libraries</li><p>
Sockets pysnmp, ncclient, paramiko, netmiko,
pyez, NAPALM.
</p><li>APIs</li><p>
Proprietary APIs, CLI, NETCONF, RETCONF.
YANG, XML, YAML, JSON.
</p><li>Other tools</li><p>
Git, GitHub, Jenkins, JIRA and others.

</p>
      </ul>

Systems & Network Training

Network & Security

Network Engineer

Higher Order Functions in Python - Level 03

<h3><b>Overview</b></h3>
<p><b>Uplift Your Career &amp; Skill Up to Your Dream Job - Learning Simplified From Home!</b></p>
<p><span>Kickstart your career &amp; boost your employability by helping you discover your skills, talents and interests with our special </span><b>Learn Python, JavaScript, and Microsoft SQL for Data science </b><span>Course. You'll create a pathway to your ideal job as this course is designed to uplift your career in the relevant industry. It provides professional training that employers are looking for in today's workplaces.</span></p>
<p><span>The </span><b>Learn Python, JavaScript, and Microsoft SQL for Data science </b><span>Course is one of the most prestigious training offered at StudyHub and is highly valued by employers for good reason. This </span><b>Learn Python, JavaScript, and Microsoft SQL for Data science </b><span>Course has been designed by industry experts to provide our learners with the best learning experience possible to increase their understanding of their chosen field.</span></p>
<p><span>This </span><b>Learn Python, JavaScript, and Microsoft SQL for Data science </b><span>Course, like every one of Study Hub's courses, is meticulously developed and well researched. Every one of the topics is divided into elementary modules, allowing our students to grasp each lesson quickly.</span></p>
<p><span>At StudyHub, we don't just offer courses; we also provide a valuable teaching process. When you buy a course from StudyHub, you get unlimited Lifetime access with 24/7 dedicated tutor support.</span></p>
<h3><b>Why buy this Learn Python, JavaScript, and Microsoft SQL for Data science?</b></h3>
<ol>
<li><span>Unlimited access to the course for forever</span></li>
<li><b>Digital Certificate, Transcript, student ID</b><span> all included in the price</span></li>
<li><span>Absolutely no hidden fees</span></li>
<li><span>Directly receive </span><b>CPD </b><span>accredited qualifications after course completion</span></li>
<li><span>Receive one to one assistance on every weekday from professionals</span></li>
<li><span>Immediately receive the PDF certificate after passing</span></li>
<li><span>Receive the original copies of your certificate and transcript on the next working day</span></li>
<li><span>Easily learn the skills and knowledge from the comfort of your home</span></li>
</ol>
<h3><b>Certification</b></h3>
<p><span>After studying the course materials of the </span><b>Learn Python, JavaScript, and Microsoft SQL for Data science</b><span> there will be a written assignment test which you can take either during or at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £5.99. Original Hard Copy certificates need to be ordered at an additional cost of £9.60.</span></p>
<h3><b>Who is this course for?</b></h3>
<p><span>This </span><b>Learn Python, JavaScript, and Microsoft SQL for Data science</b><span> course is ideal for</span></p>
<ul>
<li><span>Students</span></li>
<li><span>Recent graduates</span></li>
<li><span>Job Seekers</span></li>
<li><span>Anyone interested in this topic</span></li>
<li><span>People already working in the relevant fields and want to polish their knowledge and skill.</span></li>
</ul>
<p> </p>
<h3><b>Prerequisites</b></h3>
<p><span>This </span><b>Learn Python, JavaScript, and Microsoft SQL for Data science</b><span> does not require you to have any prior qualifications or experience. You can just enrol and start learning.This </span><b>Learn Python, JavaScript, and Microsoft SQL for Data science</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>Career path</b></h3>
<p><span>As this course comes with multiple courses included as bonus, you will be able to pursue multiple occupations. This </span><b>Learn Python, JavaScript, and Microsoft SQL for Data science </b><span>is a great way for you to gain multiple skills from the comfort of your home.</span></p>

Studyhub UK

Online Course Creation

Professional Skills Course (PSC)

Learn Python, JavaScript, and Microsoft SQL for Data science

NextGen Learning

Learn Python, JavaScript, and Microsoft SQL for Data science Course

Packt

Kali Linux

Python

Ethical Hacking

If you are a newbie in the field of ethical hacking or want to become an ethical hacker, this course is just what will get you started. This is a comprehensive course with real-world examples to help you understand the fundamentals of hacking and cyber security.

The Complete Ethical Hacking Course

<strong>This concise and comprehensive course takes you through the basic and advanced topics of Ansible, explaining all the concepts clearly and thoroughly. You will not only master the concepts but also learn how to use Ansible with cloud services and containers.</strong>
        <p>Ansible is a simple IT automation engine that automates cloud provisioning, configuration management, application deployment, intra-service orchestration, and many other IT needs. Designed for multi-tier deployments from day one, Ansible models IT infrastructure by describing how all the systems interrelate, rather than just managing one system at a time. This course will guide you through multiple topics to make you understand and master Ansible.

The course starts with the learning objectives and introduces you to Ansible. Next, you will learn how to set up the environment by installing the Ansible lab, Docker, and configuring the Secure Shell (SSH) connectivity between hosts. Moving along, you will study the architecture, modules, playbooks, and YAML Ain't Markup Language (YAML) syntaxes used in Ansible. Next, you will learn how to structure advanced Ansible playbooks and uncover techniques to use Ansible with cloud services and containers. Towards the end, you will learn how to use Ansible for validation, testing, and troubleshooting.

By the end of this course, you will have mastered the basic and advanced concepts of Ansible and will have developed the skills needed to work on real-world Ansible projects.

All the Labs and resources for this course are available at https://github.com/PacktPublishing/Dive-Into-Ansible---From-Beginner-to-Expert-in-Ansible</p>
        <h2>What You Will Learn</h2><p>Configure SSH connectivity between hosts<br>Become familiar with Ansible configuration, inventories, and modules<br>Discover how to create and execute Ansible playbooks<br>Use Ansible with cloud services and containers<br>Create a dynamic inventory with minimal scripting using Ansible<br>Use Ansible for validation, testing, and troubleshooting</p>
        <h2>Audience</h2><p>This course is designed for beginners who are looking to master the basic and advanced concepts of Ansible. There are no prerequisites for taking this course.</p>
        <h2>Approach</h2><p>With the help of hands-on exercises, examples, visual diagrams, and labs, this course will teach you the basic and advanced concepts of Ansible. You will also work on a playbook project where you will launch a website with a special Easter egg, an Ansible-themed game known as 'Playbook Stacker'.</p>
        <h2>Key Features</h2><p>Gain a solid understanding of Ansible modules and playbooks * Includes the latest Ansible version (2022 v5.x) + full lab * Learn how to use Ansible with Amazon Web Services (AWS) and Docker</p>
        <h2>Github Repo</h2><p>https://github.com/PacktPublishing/Dive-Into-Ansible---From-Beginner-to-Expert-in-Ansible</p>
        <h2>About the Author</h2><h3>James Spurin</h3><p>James Spurin is an IT professional with over 15 years of experience, working in a variety of technology fields including internet technologies, automation, software development, storage, and UNIX administration. He holds an MSc with a distinction in computer science and software engineering from Liverpool University. Professionally, he has worked for a variety of major organizations, including Dell EMC, Goldman Sachs, Nomura, and Virgin Internet. He is also an advisory board member for StorageOS, a container-based storage solution. He is an active contributor to open-source software and is the creator and maintainer of Extensible Markup Language (XML) dataset, a Python library featured on the awesome Python list for parsing XML data.</p>
        <h2>Course Outline</h2><h4>1. Course Overview and Introduction to Ansible</h4><p></p><br><h4>2. Setup of the Lab Environment and Course Resources</h4><p></p><br><h4>3. Ansible Architecture and Design</h4><p></p><br><h4>4. Ansible Playbooks, Introduction</h4><p></p><br><h4>5. Ansible Playbooks, Deep Dive</h4><p></p><br><h4>6. Structuring Ansible Playbooks</h4><p></p><br><h4>7. Using Ansible with Cloud Services and Containers</h4><p></p><br><h4>8. Creating Modules and Plugins</h4><p></p><br><h4>9. Other Ansible Resources and Areas</h4><p></p><br><h4>10. Supplementary</h4><p></p>

DevOps

Docker

Ansible

Automation

This concise and comprehensive course takes you through the basic and advanced topics of Ansible, explaining all the concepts clearly and thoroughly. You will not only master the concepts but also learn how to use Ansible with cloud services and containers.

Dive Into Ansible - From Beginner to Expert in Ansible

Online Course Marketing

Programming Fundamentals

Complete Python Machine Learning & Data Science Fundamentals

Algorithmic Trading

Investing & Trading

Making Automated Trading Bot Using Python

London

<article>
<div>
<h5>Java EVENINGS Course</h5>
</div>
<div></div>
<p>  						 
	</p><div>
	<ul>
		<p>
		<b>Python EVENINGS Course. </b>Basic Python syntax and principles of Object Orientated Programming. 
		<br />Most attendees are in-work IT Professional.
		<br />Private individuals are also very welcome. 
		<br />Evening courses also running.
		<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>6 weeks, 1 evening per week, 6pm - 8pm
		<br /><b>Times: </b>arrange a time for your time zone
	    </p>
	</ul>	

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

<div>
	  <div>
		 <h5>Python Basics EVENINGS Course </h5>
	  </div>
	  <div></div>
	  <p> 
 
				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.

<br />
This Python Programming course is hands-on and practical, to give you in-depth, practical experience of the topics covered.

	  </p>
	<div>
	<h5>Week 1: Basics</h5>
	</div>
	<div></div>
	<div> 
					<p>  <strong>Python Data Types and Variables:</strong>  
					<br />  Primitive types; Characters &amp; Strings; Boolean; Working with variables and its scope; Conversion and casting types in Python.	 
					<br /> <strong>Operators and Expressions: </strong>   
					<br />  Introduction of operators; Arithmetic operators; Relational operators; Assignment operator; Logical operators; Increment and decrement operators.
					</p> 
			 
				<p><strong> Decision Making:</strong>
				<br />If statement; If - else statement; If- elif - else statement; Nested if - else.
				</p><p><strong>Using Loops:</strong>
				<br />The while, while-else.
				<br />For loop;
				<br />Jump statements: break, continue;
				<br />Nesting loops.				
				</p>
			</div>
	<div>
	<h5>Week 2: Data Structures</h5>
	</div> <div></div>
	<div> 
				<p> Lists.
					<br />Tuples.
					<br />Sets.
					<br />Dictionary. Nested Dictionary.
					<br />Json Files.
				</p>
			</div>
	<div>
	<h5>Week 3: Python built-in functions</h5>
	</div> <div></div>
	<div> 
				<p>  
				<br />Using Built-in modules and functions:
				<br />Strings Functions.
				<br />Pattern matching with Regex.
				<br />Maths Functions.
				<br />Random Functions.
				<br />Python Date functions.
				</p>
			</div>
	<div>
	<h5>Week 4: OOP: Using Modules, functions, classes</h5>
	</div> <div></div>
	<div>
				<p>  Creating and using custom Functions.
					<br />Creating functions;
					<br />Using parameters and return values;
					<br />
					<br />Introduction to Classes and Objects:
					<br />Creating a Class; 
					<br />Creating an Object; Using an Object; 
					<br />Adding Instance variables; Controlling accessibility; Naming conventions for class members. 
					<br /> Class Constructors; Parameterized Constructors.
					<br />Inheritance. Overload.
				</p>
			</div>

	<div>
	<h5>Week 5: Pandas DataBase Basics</h5>
	</div> <div></div>
	<div>	 
		<p> <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 />Working with DDL comands:
				Create a database, drop a database.
				Create a table, alter tables, drop a table. 
				<br />Working with DML Commands:
				Insert, delete, update records.
		</p>
	</div>
	
	 
	<div>
	<h5>Week 6: Pandas Dataframe Basics</h5>
	</div> <div></div>
	<div>	 
		<p> 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,
			<br />Getting information about the dataframe,
			<br />Filter, sort and query a Dataframes,
			<br />Duplicate values,
			<br />Working with null-values,
			<br />Sampling,
			<br />Group by,
			<br />Join.

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

<div>   

	   <div id="cincluded">
		  <div>
			 <h5>What is included</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-60636103217"></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 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
  

PCWorkshops

Computer Programming

Instructor

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

General admission

<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>
	                  </div>
							 
 							<div id="eventbrite-widget-container-48024956939"></div>

							

							
							 
	               </div>
				   <div id="cincluded">
	                  <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 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

Computer Skills

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>
    <div id="widget-link">
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    </div>
</div>

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