Name: Python Programming at QLS Level 7 Course
Price: 100 GBP
Availability: InStock

<p>Are you ready to dive deep into the world of data analytics? Look no further than our Data Analytics with Tableau bundle, featuring 11 comprehensive courses that will give you the skills and knowledge needed to succeed in the world of data analysis.</p><p>Begin with the QLS-endorsed Advanced Diploma in Data Analytics with Tableau at QLS Level 6, and receive a free hardcopy certificate upon completion. This prestigious certification will set you apart from your peers.</p><p>Continue your learning journey with ten additional courses, all CPD-QS accredited, covering everything from SQL Masterclass to GDPR compliance. Our courses are designed to provide a theoretical understanding of data analytics that will serve as a strong foundation for your future career in the field.</p><p>Whether you're just starting out in data analytics or are a seasoned professional looking to expand your knowledge, our Data Analytics with Tableau bundle is the perfect choice for you. Enrol now and take the first step towards a brighter future in the exciting world of data analytics.</p><p><strong>This Data Analytics with Tableau Bundle Package includes:</strong></p><ul><li><strong>Course 01:</strong> Advanced Diploma in Data Analytics with Tableau at QLS Level 6</li></ul><p><strong>10 Premium Additional CPD QS Accredited Courses -</strong></p><ul><li><strong>Course 01:</strong> Data Analysis</li><li><strong>Course 02:</strong> SQL Masterclass: SQL For Data Analytics</li><li><strong>Course 03:</strong> Data Science &amp; Machine Learning with R Training</li><li><strong>Course 04:</strong> Google Data Studio</li><li><strong>Course 05:</strong> Excel Data Analysis</li><li><strong>Course 06:</strong> Microsoft Excel: Automated Dashboard Using Advanced Formula, VBA, Power Query</li><li><strong>Course 07:</strong> Business Intelligence and Data Mining Diploma</li><li><strong>Course 08:</strong> Business Data Analysis</li><li><strong>Course 09:</strong> Statistical Analysis</li><li><strong>Course 10:</strong> GDPR</li></ul><p><strong>Why Prefer This Data Analytics with Tableau Bundle?</strong></p><ul><li>You will receive a completely free certificate from the Quality Licence Scheme</li><li>Option to purchase 10 additional certificates accredited by CPD</li><li>Get a free Student ID Card - (£10 postal charges will be applicable for international delivery)</li><li>Free assessments and immediate success results</li><li>24/7 Tutor Support</li></ul> <p><strong>After taking this Data Analytics with Tableau</strong><strong> bundle courses, you will be able to learn:</strong></p><ul><li>Gain a thorough understanding of data analytics concepts and tools.</li><li>Master Tableau and Excel for data analysis and visualisation.</li><li>Learn how to work with SQL and relational databases for data management.</li><li>Develop skills in data science and machine learning using R.</li><li>Understand the principles of business intelligence and data mining.</li><li>Gain knowledge of statistical analysis and interpretation of results.</li><li>Acquire a comprehensive understanding of GDPR compliance and regulations.</li></ul><p><strong>***Curriculum breakdown of Data Analytics with Tableau</strong><strong>***</strong></p><ul><li><strong>Module 01:</strong> Introduction to the Course</li><li><strong>Module 02:</strong> Project 1: Discount Mart (Sales and Profit Analytics)</li><li><strong>Module 03: </strong>Project 2: Green Destinations (HR Analytics)</li><li><strong>Module 04:</strong> Project 3: Superstore (Sales Agent Tracker)</li><li><strong>Module 05: </strong>Northwind Trade (Shipping Analytics)</li><li><strong>Module 06: </strong>Project 5: Tesla (Stock Price Analytics)</li><li><strong>Module 07:</strong> Bonus: Introduction to Database Concepts</li><li><strong>Module 08: </strong>Tableau Stories</li></ul><p><strong>How is the Data Analytics with Tableau</strong><strong>Bundle Assessment Process?</strong></p><p>You have to complete the assignment questions given at the end of the course and score a minimum of 60% to pass each exam. Our expert trainers will assess your assignment and give you feedback after you submit the assignment.</p><p>You will be entitled to claim a certificate endorsed by the Quality Licence Scheme after you successfully pass the exams.</p> <h2>
        
        <div>CPD</div>
    </h2>

                        <div id="cpd">
                            <div>
                                <div>
                                    <div>
                                        250 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">
                            <ul><li>Individuals interested in pursuing a career in data analytics.</li><li>Professionals seeking to enhance their data analysis skills.</li><li>Business analysts, data scientists, and statisticians.</li><li>Anyone looking to gain a theoretical foundation in data analytics.</li></ul>
                        </div> <h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                            <ul><li>Data Analyst: £20k-£48k per year</li><li>Business Intelligence Analyst: £24k-£60k per year</li><li>Data Scientist: £33k-£75k per year</li><li>Business Analyst: £24k-£50k per year</li><li>Data Engineer: £28k-£80k per year</li><li>Statistician: £25k-£45k per year</li></ul><p>Note: Salary ranges are subject to change depending on location, experience, and industry.</p>
                        </div> <h2>
        
        <div>Certificates</div>
    </h2>

                        <div id="optional_extras">
                                    <h4>Advanced Diploma in Data Analytics with Tableau at QLS Level 6</h4>
        <p>
            Hard copy certificate -
            Included
        </p>
            <div> <p>After successfully completing the course, you can order an original hardcopy Certificate of Achievement endorsed by the <strong>Quality Licence Scheme</strong>. This certificate will be delivered to your home, free of charge.</p><p>To obtain the additional Quality License Scheme Endorsed Certificate, you will need to pay the corresponding fee based on the level of the courses:</p><ul><li>Level 1: £59</li><li>Level 2: £79</li><li>Level 3: £89</li><li>Level 4: £99</li><li>Level 5: £119</li><li>Level 6: £129</li><li>Level 7: £139</li></ul> </div>
        <h4>CPD QS Accredited Certificate</h4>
        <p>
            Digital certificate -
            £10
        </p>
            <div> <p>Upon successfully completing the Bundle, you will need to place an order to receive a PDF Certificate for each course within the bundle. These certificates serve as proof of your newly acquired skills, accredited by CPD QS and will cost you £10 for each course. Also, the certificates are recognised throughout the UK and internationally.</p> </div>
        <h4>CPD QS Accredited Certificate</h4>
        <p>
            Hard copy certificate -
            £29
        </p>
            <div> <p>International students are subject to a £10 delivery fee for their orders, based on their location.</p> </div>

                        </div>

Academy for Health and Fitness

Data Analytics with Tableau Diploma

General Admission

<div id="course-pills-1">Duration<p>1 Days</p><p>6 CPD hours</p>This course is intended for<p>This course is designed for data scientists with experience of Python who need to learn how to apply their data science and machine learning skills on Azure Databricks.</p>Overview<p>After completing this course, you will be able to:<br />Provision an Azure Databricks workspace and cluster<br />Use Azure Databricks to train a machine learning model<br />Use MLflow to track experiments and manage machine learning models<br />Integrate Azure Databricks with Azure Machine Learning</p><p>Azure Databricks is a cloud-scale platform for data analytics and machine learning. In this course, students will learn how to use Azure Databricks to explore, prepare, and model data; and integrate Databricks machine learning processes with Azure Machine Learning.<br /></p></div><div id="course-pills-2"><h4>Introduction to Azure Databricks</h4><ul><li>Getting Started with Azure Databricks</li><li>Working with Data in Azure Databricks</li></ul><h4>Training and Evaluating Machine Learning Models</h4><ul><li>Preparing Data for Machine Learning</li><li>Training a Machine Learning Model</li></ul><h4>Managing Experiments and Models</h4><ul><li>Using MLflow to Track Experiments</li><li>Managing Models</li></ul><h4>Managing Experiments and Models</h4><ul><li>Using MLflow to Track Experiments</li><li>Managing Models</li></ul><h4>Integrating Azure Databricks and Azure Machine Learning</h4><ul><li>Tracking Experiments with Azure Machine Learning</li><li>Deploying Models</li></ul></div>

Nexus Human

Microsoft AZ-900

Microsoft AZ-104

Microsoft Azure

Microsoft AZ-303

Microsoft AZ-700

Azure Machine Learning

DP-090T00: Implementing a Machine Learning Solution with Microsoft Azure Databricks

Demand for data analysts, data scientists and data engineers tripled over the past five years, rising 231%. That's much faster than job postings overall in the UK, which grew 36%. Hence, the demand for skilled data analysts has skyrocketed in the UK and worldwide! On average, salaries for these data analysts' roles are £64,376 and keep rising.
With a broader overview of the data analyst's responsibility, data chart, and presentation tools, the bundle describes how to filter, improve and handle data to present various information. You'll learn process management, how to analyse data and how to make vital business decisions. The data analyst bundle will buckle you up to perform simple to complex business analysis tasks effectively and efficiently.
Furthermore, the data analyst course accentuates developing your programming skills for a data analyst, such as Python, SQL, and R. What's more? Besides strengthening Microsoft Excel skills for a data analyst, you can improve your expertise in Tableau, Google Data Studio and business analysis ability from this Data Analyst (Data Analytics) Bundle course. Hence, you can be an efficient data analyst and a competent candidate for a challenging position.
Learning Outcomes of Data Analyst (Data Analytics)
Upon completion of the Data Analyst (Data Analytics) program, you will have acquired:
Acquire a big-picture understanding of the data analyst role
Fundamentals of data analysis (data analysis), including process management, tools for data analysis, various charts
Ability to conduct thorough research and turn raw data into presentable information
Perform many data operations in Python's famous "pandas" library, including grouping, pivoting, joining and more!
Learn about NLP, Machine Learning (ML), data visualisation using Matplotlib, Seaborn and much more
Knowledge of all the essential SQL commands and become proficient in SQL tools like GROUP BY, JOINS, and Subqueries
Become competent in using sorting and filtering commands in SQL
Learn general cloud computing concepts and gain a solid understanding of the fundamental systems on which the cloud is based
Learn how to use the R programming language for data science, machine learning, and data visualisation
Learn data analytics with Tableau, business intelligence and data mining masterclass, basic Google Data studio
This Data Analyst (Data Analytics) Bundle Consists of the following Premium courses:
Course 01: Introduction to Data Analysis
Course 02: Python for Data Analysis
Course 03: SQL Programming Masterclass
Course 04: Data Science & Machine Learning with R
Course 05: Data Analytics with Tableau
Course 06: Basic Google Data Studio
Course 07: Business Intelligence and Data Mining Masterclass
Course 08: Business Analysis Level 3
Course 09: Microsoft Excel: Automated Dashboard Using Advanced Formula, VBA, Power Query
Course 10: Cloud Computing / CompTIA Cloud+ (CV0-002)
Course 11: GDPR Data Protection Level 5
Course 12: ChatGPT Crash Course
Upon finishing this 12-course Data Analyst (Data Analytics) bundle, you will acquire the necessary skills for a thriving career in this rapidly expanding industry. Waste no more time - enrol today and commence your path towards a promising future!
The Curriculum of the Data Analyst Bundle:
Course 1: Introduction to Data Analysis
Introduction
Agenda and Principles of Process Management
The Voice of the Process
Working as One Team for Improvement
Exercise: The Voice of the Customer
Tools for Data Analysis
The Pareto Chart
The Histogram
The Run Chart
Exercise: Presenting Performance Data
Understanding Variation
The Control Chart
Control Chart Example
Control Chart Special Cases
Interpreting the Control Chart
Control Chart Exercise
Strategies to Deal with Variation
Using Data to Drive Improvement
A Structure for Performance Measurement
Exercise
Course Project
Test your Understanding
Course 2: Python for Data Analysis
Welcome, Course Introduction & overview, and
Environment set-up
Python Essentials
Python for Data Analysis using NumPy
Python for Data Analysis using Pandas
Python for Data Visualization using mat plotlib
Python for Data Visualization using Seaborn
Python for Data Visualization using pandas
Python for interactive & geographical plotting using Plotly
and Cufflinks
Capstone Project - Python for Data Analysis &
Visualisation
Python for Machine Learning (ML) - sci-kit-learn - Linear
Regression Model
Python for Machine Learning - scikit-learn - Logistic
Regression Model
Python for Machine Learning - scikit-learn - K Nearest
Neighbours
Python for Machine Learning - scikit-learn - Decision Tree
and Random Forests
Python for Machine Learning - scikit-learn -Support Vector
Machines (SVMs)
Python for Machine Learning - scikit-learn - K Means
Clustering
Python for Machine Learning - scikit-learn - Principal
Component Analysis (PCA)
Recommender Systems with Python - (Additional Topic)
Python for Natural Language Processing (NLP) - NLTK -
(Additional Topic)
Course 3: SQL Programming Masterclass
Introduction
Setting up Course Tools
Browsing & Filtering Data
Filter Data with AND, OR, NOT Operators
Math Operations
String Concatenation
Tidy Up Your Results: Sorting, Alias Names, Limit
Records
NULL, DISTINCT & CASE Statements
Functions in SQL: Multiple-Row Functions
Functions in SQL: Single-Row Functions
Nested Queries
Casting & Data Conversion
Combination Relationships
Joins in SQL
Data Manipulation (DML)
SQL Data Definition Language (DDL)
Course 4: Data Science & Machine Learning with R
Data Science and Machine Learning Course Intro
Data Types and Structures in R
Data Types and Structures in R
Intermediate R
Data Manipulation in R
Data Visualisation in R
Creating Reports with R Markdown
Building WebApps with R Shiny
Introduction to Machine Learning
Starting A Career in Data Science
Course 5: Data Analytics with Tableau
Introduction to the Course
Project 1: Discount Mart (Sales and Profit Analytics)
Project 2: Green Destinations (HR Analytics)
Project 3: Superstore (Sales Agent Tracker)
Northwind Trade (Shipping Analytics)
Project 5: Tesla (Stock Price Analytics)
Bonus: Introduction to Database Concepts
Tableau Stories
Course 6: Basic Google Data Studio
Introduction to GDS
Data Visualisation
Geo-visualisation
A Socio-Economic Case Study
Course 7: Business Intelligence and Data Mining Masterclass
What is Business Intelligence?
Starting Case in understanding BI needs in diff phases
of business
Decision-Making Process and Need for IT Systems
Problem Structure and Decision Support System
Introduction to BI Applications
Dashboard presentation systems
Different Types of Charts used in 131 Dashboards
Good Dashboard and BSC
Examples of Bad Dashboards
Process of KPI Development
Overview of Data Warehouse
More explanation of the data warehouse and steps in
processing
Data Warehouse Architecture -Tiers
Data Warehouse - components
Approach to developing data structure and Models of
database
Basics of Data Mining - Meaning
Basics of Data Mining - Stages of DM
Data Mining Technique - Classification
Data mining - Clustering
Data Mining - Association Rules
Data Mining Applications - Banking
Data Mining Applications - CRM
Data Mining Applications - other industries
Course 8: Business Analysis Level 3
Introduction to Business Analysis
Business Processes
Business Analysis Planning and Monitoring
Strategic Analysis and Product Scope
Solution Evaluation
Investigation Techniques
Ratio Analysis
Stakeholder Analysis & Management
Process Improvement with Gap Analysis
Documenting & Managing Requirements
Career Prospect as a Business Analyst in the UK
Course 9: Microsoft Excel: Automated Dashboard Using Advanced Formula, VBA, Power Query
Introduction
Prepaid Expenses Models: Resources Download
Accounting for Prepaid Expenses
Excel Formulas Detailed: Introduction to three Excel
Models
Formula-Based Prepaid Expenses Model
Calculate Prepaid Expenses Amortisation from Exact
Start Date
Prepaid Expenses Summary with Power Query & Pivot
Table
Advanced VBA Prepaid Expenses Amortisation Model
BONUS: Dynamic Dashboard for Divisional Profit &
Loss statements: Easy Way
Power Query & Pivot Tables based Dashboard without any Formulas, Fully Dynamic
Course 10: Cloud Computing CompTIA Cloud+ (CV0-002)
What You Need to Know
Introducing the Cloud
System Requirements for Cloud Deployments
Cloud Storage
Cloud Compute
Cloud Networking
Cloud Security
Migrating to the Cloud
Maintaining Cloud Solutions
Troubleshooting Cloud Solutions
Course 11: GDPR Data Protection
GDPR Basics
GDPR Explained
Lawful Basis for Preparation
Rights and Breaches
Course 12: ChatGPT Crash Course
Sign up for an OpenAI Account
What can ChatGPT do for you?
ChatGPT for Business
ChatGPT for Teaching
ChatGPT for Research
Limitations of ChatGPT
Additional Videos
 CPD 
130 CPD hours/points  Accredited by CPD Quality Standards
 Who is this course for? 
Anyone from any background can enrol in this Data Analyst (Data Analytics) bundle. Persons with similar professions can also refresh or strengthen their skills by enrolling in this Data Analyst (Data Analytics) bundle course. Students can take this course to gather professional knowledge besides their studies or for the future. 
Aspiring data analysts
Business analyst professionals who want to improve their skills
Anyone who desires to develop their data analysis skills
 
 Career path 
This Data Analyst (Data Analytics) Bundle is ideal for those who want to take their development to the next level and fast-track their career in any of the following roles:
Data Analyst: £30,000 - £50,000
Senior Data Analyst: £50,000 - £70,000
Data Scientist: £70,000 - £100,000
Business Intelligence Manager: £60,000 - £80,000
Machine Learning Engineer: £60,000 - £90,000
 Certificates 
Certificate of Completion
Digital certificate - Included
PDF certificate - Free (Previously, it was £6*12 = £72)
Certificate of Completion
Hard Copy certificate - Included
Hard Copy Certificate - Free (For The Title Course: Previously, it was £10)
Other Hard Copy certificates are available for £10 each
Please Note: The delivery charge inside the UK is £3.99, and the international students must pay a £9.99 shipping cost.

Apex Learning

Google Data Studio

GDPR

Data Mining

Tableau

Business Intelligence (BI)

Python

ChatGPT

12 in 1 Career Guided Programme | Python, Data Science, ML, Tableau, SQL Programming, Data Mining, Business Analysis | 130 CPD Points | Tutor Support | Lifetime Access

Data Analyst (Data Analytics) Diploma - CPD Certified

Kuala Lumpur

<section style="color: rgb(33, 37, 41); box-sizing: border-box;" id="isPasted" fr-original-style=" color: rgb(33, 37, 41);"><h2 style="color: rgb(62, 57, 52); box-sizing: border-box;" fr-original-style=" color: rgb(62, 57, 52);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">About this Classroom Training</strong></h2><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">In the upcoming digital era, Python stands out as the language of the future for effective AI and data analytics implementation, particularly in the Oil and Gas sector. Its widespread adoption is attributed to extensive libraries, versatility, and a thriving community of developers consistently pushing the boundaries of the field. This training course will tailor a transformative learning experience for professionals in oil and gas.</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Commencing with overview in the computer programming, participants delve into programming fundamentals and set up their Python coding environment. Participants will be able to explore flow control tools and functions, unlocking the full potential of Python. Furthermore, participants will gain expertise in various programming paradigms, with a particular focus on Object-Oriented Programming (OOP), a crucial foundation for building sophisticated applications.</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Participants will navigate through file handling, internal modules, and external libraries like NumPy, Pandas, and Matplotlib, providing proficiency in data manipulation and visualization tailored for the challenges of real-life projects. Through a hands-on Data Analytics Project, participants will apply their skills to a real-world dataset, derive insights, and present findings.</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">This comprehensive workshop equips professionals with the tools for effective automation and data analytics in the Oil and Gas sector. Participants will experience a robust understanding of Python&rsquo;s applications, ready to drive impactful and data-driven initiatives in their professional journey.</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">This course will be delivered face-to-face over 5-day sessions, comprising of 8 hours per day, 1 hour lunch and 2 breaks of 15 minutes per day. Course Duration: 8 hours in total, 40 CPD points. Maximum number of participants: 30</p><p id="isPasted" fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><a href="https://petroedgeasia.net/training/assessment-based-training-python-programming-analytics-for-the-oil-gas-sector-maximising-value-from-data-assets/" fr-original-style="" style="user-select: auto; font-size: var(--font-size); box-sizing: border-box; cursor: pointer; text-decoration: inherit;">Download your brochure</a></p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><a href="mailto:info@asiaedge.net?subject=Please Send me the Brochure for Assessment Based Training – Python Programming & Analytics for the Oil & Gas Sector – Maximising Value from Data Assets" fr-original-style="" style="user-select: auto; font-size: var(--font-size); box-sizing: border-box; cursor: pointer; text-decoration: inherit;">Email me the brochure</a></p></section><section style="color: rgb(33, 37, 41); box-sizing: border-box;" fr-original-style=" color: rgb(33, 37, 41);"><a data-toggle="collapse" href="https://petroedgeasia.net/training/assessment-based-training-python-programming-analytics-for-the-oil-gas-sector-maximising-value-from-data-assets/#collapseOne" style="color: rgb(51, 51, 51); user-select: auto; font-size: var(--font-size); box-sizing: border-box; cursor: pointer; text-decoration: inherit;" fr-original-style=" color: rgb(51, 51, 51);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">TRAINING OBJECTIVES</strong></a><div data-parent="#accordion" fr-original-style="" style="box-sizing: border-box;"><ul fr-original-style="" style="box-sizing: border-box;"><li fr-original-style="" style="box-sizing: border-box;">Acquire a comprehensive understanding of Python syntax, including variables, data types, and fundamental programming constructs.</li><li fr-original-style="" style="box-sizing: border-box;">Apply Python programming skills to analyze industry-specific datasets, extracting meaningful insights that can inform decision-making and operational efficiency.</li><li fr-original-style="" style="box-sizing: border-box;">Demonstrate the ability to automate routine tasks and streamline workflows within the Oil and Gas sector using Python.</li><li fr-original-style="" style="box-sizing: border-box;">Develop practical solutions and strategies using Python programming for challenges commonly faced in the industry, fostering hands-on experience and problem-solving capabilities.</li><li fr-original-style="" style="box-sizing: border-box;">Gain insights into emerging trends in digital technology within the industry and how Python can be leveraged for continuous adaptation and innovation.</li></ul></div><a data-toggle="collapse" href="https://petroedgeasia.net/training/assessment-based-training-python-programming-analytics-for-the-oil-gas-sector-maximising-value-from-data-assets/#collapseTwo" style="color: rgb(51, 51, 51); user-select: auto; font-size: var(--font-size); box-sizing: border-box; cursor: pointer; text-decoration: inherit;" fr-original-style=" color: rgb(51, 51, 51);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">TARGET AUDIENCE</strong></a><div data-parent="#accordion" fr-original-style="" style="box-sizing: border-box;"><ul fr-original-style="" style="box-sizing: border-box;"><li fr-original-style="" style="box-sizing: border-box;">All Engineers and Technologists from diverse fields who are interested in utilizing Python programming and data analytics techniques to explore and address challenges within their respective domains.</li><li fr-original-style="" style="box-sizing: border-box;">Data Analysts and Scientists who working with data generated by sensors, monitoring equipment, and other sources within the industry.</li><li fr-original-style="" style="box-sizing: border-box;">IT and Automation Specialists who responsible for designing and implementing IT solutions and automation systems as well as who involve in developing and maintaining software application in the Oil and Gas sector.</li><li fr-original-style="" style="box-sizing: border-box;">Executives and Managers seeking a strategic understanding of how Python and data analytics can impact decision-making and operational efficiency in the industry.</li><li fr-original-style="" style="box-sizing: border-box;">Professionals who interest in applying Python programming and data analytics techniques to study and solve challenges in the Oil and Gas field.</li><li fr-original-style="" style="box-sizing: border-box;">Individuals from related industries or backgrounds who are transitioning into roles within the Oil and Gas sector and wish to acquire relevant Python skills.</li><li fr-original-style="" style="box-sizing: border-box;">Professionals from diverse backgrounds who recognize the growing importance of data analytics in the Oil and Gas sector and wish to enhance their skill set.</li></ul></div><a data-toggle="collapse" href="https://petroedgeasia.net/training/assessment-based-training-python-programming-analytics-for-the-oil-gas-sector-maximising-value-from-data-assets/#collapsecl" style="color: rgb(51, 51, 51); user-select: auto; font-size: var(--font-size); box-sizing: border-box; cursor: pointer; text-decoration: inherit;" fr-original-style=" color: rgb(51, 51, 51);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">COURSE LEVEL</strong></a><div data-parent="#accordion" fr-original-style="" style="box-sizing: border-box;"><ul fr-original-style="" style="box-sizing: border-box;"><li fr-original-style="" style="box-sizing: border-box;">Basic</li><li fr-original-style="" style="box-sizing: border-box;">Intermediate</li></ul></div><a data-toggle="collapse" href="https://petroedgeasia.net/training/assessment-based-training-python-programming-analytics-for-the-oil-gas-sector-maximising-value-from-data-assets/#collapseThree" style="color: rgb(51, 51, 51); user-select: auto; font-size: var(--font-size); box-sizing: border-box; cursor: pointer; text-decoration: inherit;" fr-original-style=" color: rgb(51, 51, 51);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">TRAINING METHODS</strong></a><div data-parent="#accordion" 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;">The trainer will employ the &lsquo;learning by doing&rsquo; method by emphasizing practical application. Participants will be introduced to the concepts and theories using techniques that they can easily relate to. The learning experience is then reinforced by implementing the subject through real-life examples. The trainer will provide quizzes and tests for self-assessment and ensuring participants can measure their understanding and apply the knowledge effectively. This hands-on approach not only enhances comprehension but also empowers participants to confidently apply the learned skills in their professional endeavors.</p><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;">Preparation ahead of the Class:</strong></p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Participants are required to download the&nbsp;<strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Python 3.x</strong>&nbsp;version software onto their laptops.</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">The instructions are provided below:</p><ol fr-original-style="" style="box-sizing: border-box;"><li fr-original-style="" style="box-sizing: border-box;">Download&nbsp;<strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Anaconda</strong>&nbsp;by visiting the Anaconda website (https://www.anaconda.com/products/distribution).</li><li fr-original-style="" style="box-sizing: border-box;">Click on the &ldquo;<strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Download</strong>&rdquo; button for the version that suits your operating system (Windows, macOS, Linux).</li><li fr-original-style="" style="box-sizing: border-box;">&nbsp;Select the&nbsp;<strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Python 3.x</strong>&nbsp;version (e.g., Python 3.8) during the installation process.</li><li fr-original-style="" style="box-sizing: border-box;">Install Anaconda follow the instructions to run the installer. Install Just Me (Recommended).</li></ol></div><a data-toggle="collapse" href="https://petroedgeasia.net/training/assessment-based-training-python-programming-analytics-for-the-oil-gas-sector-maximising-value-from-data-assets/#collapseFive" style="color: rgb(51, 51, 51); user-select: auto; font-size: var(--font-size); box-sizing: border-box; cursor: pointer; text-decoration: inherit;" fr-original-style=" color: rgb(51, 51, 51);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">TRAINER</strong></a><div data-parent="#accordion" 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;">Your expert trainer is a seasoned multidisciplinary engineer with a 15-year professional journey, driven by an unwavering commitment to innovation and excellence. Armed with a Ph.D. in offshore engineering, he draws extensive insights from diverse industry sectors, notably oil and gas, where he served as a subsea pipeline engineer. His hands-on experience encompasses the entire spectrum, from design and manufacturing to installation and operations of offshore oil and gas facilities.</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Previously at Rosen Group, your expert trainer developed digital tools for offshore structural assessments and risk-based inspection. He led research at the ARC Offshore Floating Facilities Hub on enhancing riser design and monitoring using Python and data analytics. He performed design verification for INPEX, Chevron, and Apache on subsea pipelines, risers, umbilicals, and LNG facilities, and was a deputy project manager on verifying the Ichthys gas pipeline. He conducted risk-based inspection and auditing of the Ichthys LNG plant for DNV GL. He also worked as a structural engineer at Advanced Building Engineers designing steel structures, buildings, and other components. Meanwhile, at the University of Western Australia (UWA), your expert trainer developed AI and data solutions for the oil &amp; gas industry focused on condition monitoring and probabilistic assessments and led research on offshore facilities by creating tools for analysis and machine learning.</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">His academic pursuit culminated in a thesis that underscores his proficiency in employing data science and machine learning, primarily through Python. His research focused on optimising asset integrity management for offshore oil and gas assets, showcasing a seamless integration of engineering and cutting-edge technology. In 2023, he fully unleash AI-driven solutions across diverse sectors. Currently, he actively contributes to mineral resource exploration and assists oil and gas operators in the effective implementation of new AI and digital technologies.</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">His dedication to knowledge dissemination is evident through his role as a global educator. Over the past five years, he has conducted Python programming lectures at universities and industries, reaching over 1000 novices. His unwavering commitment to lifelong learning, coupled with a growth mindset have positions him as a transformative trainer in the realms of applied AI, data science, and engineering in oil and gas sector</p><section style="color: rgb(33, 37, 41); box-sizing: border-box;" id="isPasted" fr-original-style=" color: rgb(33, 37, 41);"><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><a href="https://petroedgeasia.net/training/assessment-based-training-python-programming-analytics-for-the-oil-gas-sector-maximising-value-from-data-assets/" fr-original-style="" style="user-select: auto; font-size: var(--font-size); box-sizing: border-box; cursor: pointer; text-decoration: inherit;">Download your brochure</a></p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><a href="mailto:info@asiaedge.net?subject=Please Send me the Brochure for Assessment Based Training – Python Programming & Analytics for the Oil & Gas Sector – Maximising Value from Data Assets" fr-original-style="" style="user-select: auto; font-size: var(--font-size); box-sizing: border-box; cursor: pointer; text-decoration: inherit;">Email me the brochure</a></p></section></div><a data-toggle="collapse" href="https://petroedgeasia.net/training/assessment-based-training-python-programming-analytics-for-the-oil-gas-sector-maximising-value-from-data-assets/#collapseCS" style="color: rgb(51, 51, 51); user-select: auto; font-size: var(--font-size); box-sizing: border-box; cursor: pointer; text-decoration: inherit;" fr-original-style=" color: rgb(51, 51, 51);">POST TRAINING COACHING SUPPORT (OPTIONAL)</a><div data-parent="#accordion" 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;">To further optimise your learning experience from our courses, we also offer individualized &ldquo;One to One&rdquo; coaching support for 2 hours post training. We can help improve your competence in your chosen area of interest, based on your learning needs and available hours. This is a great opportunity to improve your capability and confidence in a particular area of expertise. It will be delivered over a secure video conference call by one of our senior trainers. They will work with you to create a tailor-made coaching program that will help you achieve your goals faster.<br fr-original-style="" style="box-sizing: border-box;"><a href="mailto:info@asiaedge.net?subject=Request%20for%20further%20information%20regarding%20post%20training%20coaching%20support" target="_blank" style="color: rgb(0, 123, 255); user-select: auto; font-size: var(--font-size); box-sizing: border-box; cursor: pointer; text-decoration: inherit;" fr-original-style=" color: rgb(0, 123, 255);">Request for further information post training support</a>&nbsp;and fees applicable.</p></div></section>

EnergyEdge - Training for a Sustainable Energy Future

Machine Learning (ML)

Maximize the value of data assets in the oil and gas sector with EnergyEdge's assessment-based training course on Python programming and analytics.

Assessment Based Training - Python Programming & Analytics for the Oil & Gas Sector - Maximising Value from Data Assets

Team of 10, pp

Normal Fee, pp

<section style="color: rgb(33, 37, 41); box-sizing: border-box;" id="isPasted" fr-original-style=" color: rgb(33, 37, 41);"><h2 style="color: rgb(62, 57, 52); box-sizing: border-box;" fr-original-style=" color: rgb(62, 57, 52);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">About this Classroom Training</strong></h2><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">In the upcoming digital era, Python stands out as the language of the future for effective AI and data analytics implementation, particularly in the Oil and Gas sector. Its widespread adoption is attributed to extensive libraries, versatility, and a thriving community of developers consistently pushing the boundaries of the field. This training course will tailor a transformative learning experience for professionals in oil and gas.</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Commencing with overview in the computer programming, participants delve into programming fundamentals and set up their Python coding environment. Participants will be able to explore flow control tools and functions, unlocking the full potential of Python. Furthermore, participants will gain expertise in various programming paradigms, with a particular focus on Object-Oriented Programming (OOP), a crucial foundation for building sophisticated applications.</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Participants will navigate through file handling, internal modules, and external libraries like NumPy, Pandas, and Matplotlib, providing proficiency in data manipulation and visualization tailored for the challenges of real-life projects. Through a hands-on Data Analytics Project, participants will apply their skills to a real-world dataset, derive insights, and present findings.</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">This comprehensive workshop equips professionals with the tools for effective automation and data analytics in the Oil and Gas sector. Participants will experience a robust understanding of Python&rsquo;s applications, ready to drive impactful and data-driven initiatives in their professional journey.</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">This course will be delivered face-to-face over 5-day sessions, comprising of 8 hours per day, 1 hour lunch and 2 breaks of 15 minutes per day. Course Duration: 8 hours in total, 40 CPD points. Maximum number of participants: 30</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><a href="https://petroedgeasia.net/training/assessment-based-training-python-programming-analytics-for-the-oil-gas-sector-maximising-value-from-data-assets/" fr-original-style="" style="user-select: auto; font-size: var(--font-size); box-sizing: border-box; cursor: pointer; text-decoration: inherit;">Download your brochure</a></p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><a href="mailto:info@asiaedge.net?subject=Please Send me the Brochure for Assessment Based Training – Python Programming & Analytics for the Oil & Gas Sector – Maximising Value from Data Assets" fr-original-style="" style="user-select: auto; font-size: var(--font-size); box-sizing: border-box; cursor: pointer; text-decoration: inherit;">Email me the brochure</a></p></section><section style="color: rgb(33, 37, 41); box-sizing: border-box;" fr-original-style=" color: rgb(33, 37, 41);"><a data-toggle="collapse" href="https://petroedgeasia.net/training/assessment-based-training-python-programming-analytics-for-the-oil-gas-sector-maximising-value-from-data-assets/#collapseOne" style="color: rgb(51, 51, 51); user-select: auto; font-size: var(--font-size); box-sizing: border-box; cursor: pointer; text-decoration: inherit;" fr-original-style=" color: rgb(51, 51, 51);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">TRAINING OBJECTIVES</strong></a><div data-parent="#accordion" fr-original-style="" style="box-sizing: border-box;"><ul fr-original-style="" style="box-sizing: border-box;"><li fr-original-style="" style="box-sizing: border-box;">Acquire a comprehensive understanding of Python syntax, including variables, data types, and fundamental programming constructs.</li><li fr-original-style="" style="box-sizing: border-box;">Apply Python programming skills to analyze industry-specific datasets, extracting meaningful insights that can inform decision-making and operational efficiency.</li><li fr-original-style="" style="box-sizing: border-box;">Demonstrate the ability to automate routine tasks and streamline workflows within the Oil and Gas sector using Python.</li><li fr-original-style="" style="box-sizing: border-box;">Develop practical solutions and strategies using Python programming for challenges commonly faced in the industry, fostering hands-on experience and problem-solving capabilities.</li><li fr-original-style="" style="box-sizing: border-box;">Gain insights into emerging trends in digital technology within the industry and how Python can be leveraged for continuous adaptation and innovation.</li></ul></div><a data-toggle="collapse" href="https://petroedgeasia.net/training/assessment-based-training-python-programming-analytics-for-the-oil-gas-sector-maximising-value-from-data-assets/#collapseTwo" style="color: rgb(51, 51, 51); user-select: auto; font-size: var(--font-size); box-sizing: border-box; cursor: pointer; text-decoration: inherit;" fr-original-style=" color: rgb(51, 51, 51);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">TARGET AUDIENCE</strong></a><div data-parent="#accordion" fr-original-style="" style="box-sizing: border-box;"><ul fr-original-style="" style="box-sizing: border-box;"><li fr-original-style="" style="box-sizing: border-box;">All Engineers and Technologists from diverse fields who are interested in utilizing Python programming and data analytics techniques to explore and address challenges within their respective domains.</li><li fr-original-style="" style="box-sizing: border-box;">Data Analysts and Scientists who working with data generated by sensors, monitoring equipment, and other sources within the industry.</li><li fr-original-style="" style="box-sizing: border-box;">IT and Automation Specialists who responsible for designing and implementing IT solutions and automation systems as well as who involve in developing and maintaining software application in the Oil and Gas sector.</li><li fr-original-style="" style="box-sizing: border-box;">Executives and Managers seeking a strategic understanding of how Python and data analytics can impact decision-making and operational efficiency in the industry.</li><li fr-original-style="" style="box-sizing: border-box;">Professionals who interest in applying Python programming and data analytics techniques to study and solve challenges in the Oil and Gas field.</li><li fr-original-style="" style="box-sizing: border-box;">Individuals from related industries or backgrounds who are transitioning into roles within the Oil and Gas sector and wish to acquire relevant Python skills.</li><li fr-original-style="" style="box-sizing: border-box;">Professionals from diverse backgrounds who recognize the growing importance of data analytics in the Oil and Gas sector and wish to enhance their skill set.</li></ul></div><a data-toggle="collapse" href="https://petroedgeasia.net/training/assessment-based-training-python-programming-analytics-for-the-oil-gas-sector-maximising-value-from-data-assets/#collapsecl" style="color: rgb(51, 51, 51); user-select: auto; font-size: var(--font-size); box-sizing: border-box; cursor: pointer; text-decoration: inherit;" fr-original-style=" color: rgb(51, 51, 51);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">COURSE LEVEL</strong></a><div data-parent="#accordion" fr-original-style="" style="box-sizing: border-box;"><ul fr-original-style="" style="box-sizing: border-box;"><li fr-original-style="" style="box-sizing: border-box;">Basic</li><li fr-original-style="" style="box-sizing: border-box;">Intermediate</li></ul></div><a data-toggle="collapse" href="https://petroedgeasia.net/training/assessment-based-training-python-programming-analytics-for-the-oil-gas-sector-maximising-value-from-data-assets/#collapseThree" style="color: rgb(51, 51, 51); user-select: auto; font-size: var(--font-size); box-sizing: border-box; cursor: pointer; text-decoration: inherit;" fr-original-style=" color: rgb(51, 51, 51);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">TRAINING METHODS</strong></a><div data-parent="#accordion" 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;">The trainer will employ the &lsquo;learning by doing&rsquo; method by emphasizing practical application. Participants will be introduced to the concepts and theories using techniques that they can easily relate to. The learning experience is then reinforced by implementing the subject through real-life examples. The trainer will provide quizzes and tests for self-assessment and ensuring participants can measure their understanding and apply the knowledge effectively. This hands-on approach not only enhances comprehension but also empowers participants to confidently apply the learned skills in their professional endeavors.</p><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;">Preparation ahead of the Class:</strong></p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Participants are required to download the <strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Python 3.x</strong> version software onto their laptops.</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">The instructions are provided below:</p><ol fr-original-style="" style="box-sizing: border-box;"><li fr-original-style="" style="box-sizing: border-box;">Download <strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Anaconda</strong> by visiting the Anaconda website (https://www.anaconda.com/products/distribution).</li><li fr-original-style="" style="box-sizing: border-box;">Click on the &ldquo;<strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Download</strong>&rdquo; button for the version that suits your operating system (Windows, macOS, Linux).</li><li fr-original-style="" style="box-sizing: border-box;">&nbsp;Select the <strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Python 3.x</strong> version (e.g., Python 3.8) during the installation process.</li><li fr-original-style="" style="box-sizing: border-box;">Install Anaconda follow the instructions to run the installer. Install Just Me (Recommended).</li></ol></div><a data-toggle="collapse" href="https://petroedgeasia.net/training/assessment-based-training-python-programming-analytics-for-the-oil-gas-sector-maximising-value-from-data-assets/#collapseFive" style="color: rgb(51, 51, 51); user-select: auto; font-size: var(--font-size); box-sizing: border-box; cursor: pointer; text-decoration: inherit;" fr-original-style=" color: rgb(51, 51, 51);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">TRAINER</strong></a><div data-parent="#accordion" 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;">Your expert trainer is a seasoned multidisciplinary engineer with a 15-year professional journey, driven by an unwavering commitment to innovation and excellence. Armed with a Ph.D. in offshore engineering, he draws extensive insights from diverse industry sectors, notably oil and gas, where he served as a subsea pipeline engineer. His hands-on experience encompasses the entire spectrum, from design and manufacturing to installation and operations of offshore oil and gas facilities.</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Previously at Rosen Group, your expert trainer developed digital tools for offshore structural assessments and risk-based inspection. He led research at the ARC Offshore Floating Facilities Hub on enhancing riser design and monitoring using Python and data analytics. He performed design verification for INPEX, Chevron, and Apache on subsea pipelines, risers, umbilicals, and LNG facilities, and was a deputy project manager on verifying the Ichthys gas pipeline. He conducted risk-based inspection and auditing of the Ichthys LNG plant for DNV GL. He also worked as a structural engineer at Advanced Building Engineers designing steel structures, buildings, and other components. Meanwhile, at the University of Western Australia (UWA), your expert trainer developed AI and data solutions for the oil &amp; gas industry focused on condition monitoring and probabilistic assessments and led research on offshore facilities by creating tools for analysis and machine learning.</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">His academic pursuit culminated in a thesis that underscores his proficiency in employing data science and machine learning, primarily through Python. His research focused on optimising asset integrity management for offshore oil and gas assets, showcasing a seamless integration of engineering and cutting-edge technology. In 2023, he fully unleash AI-driven solutions across diverse sectors. Currently, he actively contributes to mineral resource exploration and assists oil and gas operators in the effective implementation of new AI and digital technologies.</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">His dedication to knowledge dissemination is evident through his role as a global educator. Over the past five years, he has conducted Python programming lectures at universities and industries, reaching over 1000 novices. His unwavering commitment to lifelong learning, coupled with a growth mindset have positions him as a transformative trainer in the realms of applied AI, data science, and engineering in oil and gas sector</p><section style="color: rgb(33, 37, 41); box-sizing: border-box;" fr-original-style=" color: rgb(33, 37, 41);"><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><a href="https://petroedgeasia.net/training/assessment-based-training-python-programming-analytics-for-the-oil-gas-sector-maximising-value-from-data-assets/" fr-original-style="" style="user-select: auto; font-size: var(--font-size); box-sizing: border-box; cursor: pointer; text-decoration: inherit;">Download your brochure</a></p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><a href="mailto:info@asiaedge.net?subject=Please Send me the Brochure for Assessment Based Training – Python Programming & Analytics for the Oil & Gas Sector – Maximising Value from Data Assets" fr-original-style="" style="user-select: auto; font-size: var(--font-size); box-sizing: border-box; cursor: pointer; text-decoration: inherit;">Email me the brochure</a></p></section></div><a data-toggle="collapse" href="https://petroedgeasia.net/training/assessment-based-training-python-programming-analytics-for-the-oil-gas-sector-maximising-value-from-data-assets/#collapseCS" style="color: rgb(51, 51, 51); user-select: auto; font-size: var(--font-size); box-sizing: border-box; cursor: pointer; text-decoration: inherit;" fr-original-style=" color: rgb(51, 51, 51);">POST TRAINING COACHING SUPPORT (OPTIONAL)</a><div data-parent="#accordion" 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;">To further optimise your learning experience from our courses, we also offer individualized &ldquo;One to One&rdquo; coaching support for 2 hours post training. We can help improve your competence in your chosen area of interest, based on your learning needs and available hours. This is a great opportunity to improve your capability and confidence in a particular area of expertise. It will be delivered over a secure video conference call by one of our senior trainers. They will work with you to create a tailor-made coaching program that will help you achieve your goals faster.<br fr-original-style="" style="box-sizing: border-box;"><a href="mailto:info@asiaedge.net?subject=Request%20for%20further%20information%20regarding%20post%20training%20coaching%20support" target="_blank" style="color: rgb(0, 123, 255); user-select: auto; font-size: var(--font-size); box-sizing: border-box; cursor: pointer; text-decoration: inherit;" fr-original-style=" color: rgb(0, 123, 255);">Request for further information post training support</a> and fees applicable.</p></div></section>

Assessment Based Training – Python Programming & Analytics for the Oil & Gas Sector – Maximising Value from Data Assets

<strong>This course will be mainly focusing on machine learning algorithms. Throughout this course, we are preparing our machine to make it ready for a prediction test.</strong>
        <p>Artificial intelligence, machine learning, and deep learning neural networks are the most used terms in the technology world today. They're also the most misunderstood and confused terms. Artificial intelligence is a broad spectrum of science that tries to make machines intelligent like humans, while machine learning and neural networks are two subsets that sit within this vast machine learning platform. But in this course, you will focus mainly on machine learning, which will include preparing your machine to make it ready for a prediction test.
You will be using Python as your programming language. Python is a great tool for the development of programs that perform data analysis and prediction. It has a variety of classes and features that perform complex mathematical analyses and provide solutions in just a few lines of code, making it easier for you to get up to speed with data science and machine learning.

Machine learning and data science jobs are among the most lucrative in the technology industry in recent times. Exploring this course will help you get well-versed with essential concepts and prepare you for a career in these fields.

All the code and supporting files for this course are available at https://github.com/PacktPublishing/Machine-Learning-and-Data-Science-with-Python-A-Complete-Beginners-Guide</p>
        <h2>What You Will Learn</h2><p>Install Python and required libraries<br>Choose the best machine learning model<br>Automate and combine workflows with pipeline<br>Look at performance improvement with ensembles<br>Study performance improvement with algorithm parameter tuning<br>Finalize a machine learning project</p>
        <h2>Audience</h2><p>This course is for beginners who are interested in machine learning using Python.</p>
        <h2>Approach</h2><p>An exhaustive course packed with step-by-step instructions, working examples, and helpful advice. This course is divided into clear chunks so you can learn at your own pace and focus on your own area of interest.</p>
        <h2>Key Features</h2><p>Learn machine learning and data science using Python * A practical course designed for beginners who are interested in machine learning using Python * Work on predictions and case studies</p>
        <h2>Github Repo</h2><p>https://github.com/packtpublishing/machine-learning-and-data-science-with-python-a-complete-beginners-guide</p>
        <h2>About the Author</h2><h3>Abhilash Nelson </h3><p>Abhilash Nelson is a pioneering, talented, and security-oriented Android/iOS mobile and PHP/Python web application developer with more than eight years of IT experience involving designing, implementing, integrating, testing, and supporting impactful web and mobile applications. He has a master's degree in computer science and engineering and has PHP/Python programming experience, which is an added advantage for server-based Android and iOS client applications. Abhilash is currently a senior solution architect managing projects from start to finish to ensure high quality and innovative and functional design.</p>
        <h2>Course Outline</h2><h4>1. Course Overview and Table of Contents</h4><p></p><br><h4>2. Introduction to Machine Learning</h4><p></p><br><h4>3. System and Environment Preparation</h4><p></p><br><h4>4. Learn Basics of Python</h4><p></p><br><h4>5. Learn Basics of NumPy</h4><p></p><br><h4>6. Learn Basics of Matplotlib</h4><p></p><br><h4>7. Learn Basics of Pandas</h4><p></p><br><h4>8. Understanding the CSV Data File</h4><p></p><br><h4>9. Load and Read CSV Data File</h4><p></p><br><h4>10. Dataset Summary</h4><p></p><br><h4>11. Dataset Visualization</h4><p></p><br><h4>12. Data Preparation</h4><p></p><br><h4>13. Feature Selection</h4><p></p><br><h4>14. Refresher Session - the Mechanism of Re-Sampling, Training, and Testing</h4><p></p><br><h4>15. Algorithm Evaluation Techniques</h4><p></p><br><h4>16. Algorithm Evaluation Metrics</h4><p></p><br><h4>17. Classification Algorithm Spot Check - Logistic Regression</h4><p></p><br><h4>18. Classification Algorithm Spot Check - Linear Discriminant Analysis</h4><p></p><br><h4>19. Classification Algorithm Spot Check - K-Nearest Neighbors</h4><p></p><br><h4>20. Classification Algorithm Spot Check - Naive Bayes</h4><p></p><br><h4>21. Classification Algorithm Spot Check - CART</h4><p></p><br><h4>22. Classification Algorithm Spot Check - Support Vector Machines</h4><p></p><br><h4>23. Regression Algorithm Spot Check - Linear Regression</h4><p></p><br><h4>24. Regression Algorithm Spot Check - Ridge Regression</h4><p></p><br><h4>25. Regression Algorithm Spot Check - LASSO Linear Regression</h4><p></p><br><h4>26. Regression Algorithm Spot Check - Elastic Net Regression</h4><p></p><br><h4>27. Regression Algorithm Spot Check - K-Nearest Neighbors</h4><p></p><br><h4>28. Regression Algorithm Spot Check - CART</h4><p></p><br><h4>29. Regression Algorithm Spot Check - Support Vector Machines (SVM)</h4><p></p><br><h4>30. Compare Algorithms - Part 1: Choosing the Best Machine Learning Model</h4><p></p><br><h4>31. Compare Algorithms - Part 2: Choosing the Best Machine Learning Model</h4><p></p><br><h4>32. Pipelines: Data Preparation and Data Modelling</h4><p></p><br><h4>33. Pipelines: Feature Selection and Data Modelling</h4><p></p><br><h4>34. Performance Improvement: Ensembles - Voting</h4><p></p><br><h4>35. Performance Improvement: Ensembles - Bagging</h4><p></p><br><h4>36. Performance Improvement: Ensembles - Boosting</h4><p></p><br><h4>37. Performance Improvement: Parameter Tuning Using Grid Search</h4><p></p><br><h4>38. Performance Improvement: Parameter Tuning Using Random Search</h4><p></p><br><h4>39. Export, Save and Load Machine Learning Models: Pickle</h4><p></p><br><h4>40. Export, Save and Load Machine Learning Models: Joblib</h4><p></p><br><h4>41. Finalizing a Model - Introduction and Steps</h4><p></p><br><h4>42. Finalizing a Classification Model - the Pima Indian Diabetes Dataset</h4><p></p><br><h4>43. Quick Session: Imbalanced Dataset - Issue Overview and Steps</h4><p></p><br><h4>44. Iris Dataset: Finalizing Multi-Class Dataset</h4><p></p><br><h4>45. Finalizing a Regression Model - the Boston Housing Price Dataset</h4><p></p><br><h4>46. Real-Time Predictions: Using the Pima Indian Diabetes Classification Model</h4><p></p><br><h4>47. Real-time Predictions: Using Iris Flowers Multi-Class Classification Dataset</h4><p></p><br><h4>48. Real-Time Predictions: Using the Boston Housing Regression Model</h4><p></p>

Packt

Data Science

This course will be mainly focusing on machine learning algorithms. Throughout this course, we are preparing our machine to make it ready for a prediction test.

Machine Learning and Data Science with Python: A Complete Beginners Guide

<p><strong>24 Hours Left! Don't Let Winter Sale Slip Away - Enrol Now!</strong></p><p><strong>With over 100,000 civil engineers in the UK, the demand for data-savvy professionals is high. According to a recent study, 72% of UK civil engineering firms are investing in data analytics to enhance decision-making processes, with data engineering experiencing a 40% year-on-year growth.</strong></p><p>This surge outpaces other tech sectors, highlighting the critical role of data engineers in big data and advanced analytics. This Data Engineering bundle empowers you to capitalise on this growing trend, equipping you with the proficiency to extract valuable insights from vast datasets, optimise project planning, and enhance overall efficiency.</p><p>Embark on a transformative journey with our Data Engineering Bundle, thoroughly crafted to bridge the skill gap in one of the UK's fastest-growing job markets. Our bundle offers a comprehensive exploration into the world of data, equipping you with the analytical prowess to harness, process, and visualise data effectively. From mastering SQL programming to delving into the complexities of machine learning with R, this bundle is your gateway to becoming a data engineering maestro.</p><p>In today's data-driven landscape, possessing a robust set of analytical skills is no longer a luxury but a necessity. With an emphasis on Data engineering, our courses are designed to foster a deep understanding of data analytics, visualisation, and mining, ensuring you can convert raw data into strategic insights that propel business decisions.</p><p>Seize the opportunity to be at the helm of innovation and become the architect of tomorrow's data landscape with our Data Engineering Bundle. Join us now!</p><p><strong>Courses are Included in This Data Engineering Bundle:</strong></p><ul><li><strong> Course 01: </strong>Introduction to Data Analysis</li><li><strong> Course 02: </strong>Data Science &amp; Machine Learning with R</li><li><strong> Course 03: </strong>Data Analytics with Tableau</li><li><strong> Course 04: </strong>SQL Programming Masterclass</li><li><strong> Course 05: </strong>Excel Pivot table for Data analytics</li><li><strong> Course 06: </strong>Data analytics with Excel</li><li><strong> Course 07: </strong>Python for Data Analysis</li><li><strong> Course 08: </strong>Basic Google Data Studio</li><li><strong> Course 09: </strong>Business Intelligence and Data Mining Masterclass</li><li><strong> Course 10: </strong>Microsoft Excel: Automated Dashboard Using Advanced Formula, VBA, Power Query</li><li><strong> Course 11: </strong>JavaScript Functions for Data Analyst</li><li><strong> Course 12: </strong>GDPR Data Protection Level 5</li><li><strong> Course 13: </strong>GDPR Training</li><li><strong> Course 14: </strong>Learn Programming with Python</li><li><strong> Course 15: </strong>Data Center Training Essentials: General Introduction</li><li><strong> Course 16: </strong>Quick Data Science Approach from Scratch</li><li><strong> Course 17: </strong>Statistics &amp; Probability for Data Science &amp; Machine Learning</li><li><strong> Course 18: </strong>Master JavaScript with Data Visualization</li><li><strong> Course 19: </strong>Excel Data Tools and Data Management</li><li><strong> Course 20: </strong>Cloud Computing Essentials for Data Analysis</li></ul><p><strong>Learning Outcomes of Data Engineering Bundle:</strong></p><ul><li>Gain proficiency in SQL for complex database management and analytics tasks.</li><li>Master R for data science and machine learning applications in various industries.</li><li>Develop advanced Excel skills, including data analytics and pivot table expertise.</li><li>Acquire hands-on experience with Tableau for effective data visualisation.</li><li>Learn Python programming essentials for data analysis and engineering solutions.</li><li>Understand Google Data Studio to create dynamic reports and dashboards.</li></ul><p><strong>Why Choose Our Data Engineering Course?</strong></p><ul><li>FREE Data Engineering certificate accredited</li><li>Get a free student ID card with Data Engineering Training</li><li>Get instant access to this Data Engineering course.</li><li>Learn Data Engineering from anywhere in the world</li><li>The Data Engineering is affordable and simple to understand</li><li>The Data Engineering is an entirely online, interactive lesson with voiceover audio</li><li>Lifetime access to the Data Engineering course materials</li><li>The Data Engineering comes with 24/7 tutor support</li></ul> <p><strong>Start your learning journey straightaway with our Data Engineering Bundle!</strong></p><p>This Data Engineering bundle will equip you with the skills and knowledge to become a data-savvy civil engineer. You will learn how to collect, analyze, and interpret data to improve infrastructure projects and processes. This Data Engineering bundle includes courses on data analysis, data science, machine learning, SQL programming, Excel pivot tables, Excel data analytics, Python for data analysis, Google Data Studio, business intelligence, data mining, GDPR data protection, JavaScript functions for data analysts, and Python programming.</p><p><strong>Assessment Process of Data Engineering</strong></p><p>Once you have completed all the courses in the Data Engineering bundle, you can assess your skills and knowledge with an optional assignment. Our expert trainers will assess your assignment and give you feedback afterwards.</p> <h2>
        
        <div>CPD</div>
    </h2>

                        <div id="cpd">
                            <div>
                                <div>
                                    <div>
                                        200 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>This Data Engineering bundle is suitable for everyone. Also, our Data Engineering Bundle is perfect for:</p><ul><li>Aspiring data engineers</li><li>Business intelligence analysts</li><li>Data-driven marketers</li><li>IT professionals</li><li>Statistics enthusiasts</li><li>Career changers</li></ul>
                        </div> <h2>
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                            <p>You will not need any prior background or expertise in the Data Engineering Bundle.</p>
                        </div> <h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                            <p>This Data Engineering bundle will allow you to kickstart or take your career to the next stage in the related sector such as:</p><ul><li><strong>Data Analyst</strong></li><li><strong>BI Developer</strong></li><li><strong>ML Engineer</strong></li><li><strong>Data Scientist</strong></li><li><strong>Database Administrator</strong></li><li><strong>Data Strategist</strong></li></ul>
                        </div> <h2>
        
        <div>Certificates</div>
    </h2>

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

                        </div>

Data Engineering - CPD Certified

<p>Get ready for an exceptional online learning experience with the <strong>Python, Data Science, Machine Learning, SQL, Cloud computing &amp; Cyber Security </strong>bundle! This carefully curated collection of<strong> 20 premium courses</strong> is designed to cater to a variety of interests and disciplines. Dive into a sea of knowledge and skills, tailoring your learning journey to suit your unique aspirations.</p><p>The Python &amp; Data Science package is dynamic, blending the expertise of industry professionals with the flexibility of digital learning. It offers the perfect balance of foundational understanding and advanced insights. Whether you're looking to break into a new field or deepen your existing knowledge, the Python, Data Science, Machine Learning, SQL, Cloud computing &amp; Cyber Securitypackage has something for everyone.</p><p>As part of the Python &amp; Data Science package, you will receive complimentary PDF certificates for all courses in this bundle at no extra cost. Equip yourself with the Python &amp; Data Science bundle to confidently navigate your career path or personal development journey. Enrol today and start your career growth!</p><p><strong>This Bundle Comprises the Following </strong><strong>Python, Data Science, Machine Learning, SQL, Cloud computing &amp; Cyber Security  </strong><strong>CPD-accredited courses:</strong></p><ul><li><strong>Course 01: </strong>Python Programming: Beginner To Expert</li><li><strong>Course 02:</strong> Data Science &amp; Machine Learning with Python</li><li><strong>Course 03: </strong>Coding with Python 3</li><li><strong>Course 04: </strong>Introduction to Coding With HTML, CSS, &amp; Javascript</li><li><strong>Course 05: </strong>Python for Spatial Analysis in ArcGIS</li><li><strong>Course 06: </strong>Python Programming Bible | Networking, GUI, Email, XML, CGI</li><li><strong>Course 07: </strong>Business Intelligence and Data Mining</li><li><strong>Course 08: </strong>SQL for Data Science, Data Analytics and Data Visualization</li><li><strong>Course 09: </strong>Python Data Science with Numpy, Pandas and Matplotlib</li><li><strong>Course 10: </strong>Cloud Computing / CompTIA Cloud+ (CV0-002)</li><li><strong>Course 11: </strong>Cyber Security Awareness Training</li><li><strong>Course 12:</strong> Learn Ethical Hacking From A-Z: Beginner To Expert</li><li><strong>Course 13: </strong>Easy to Advanced Data Structures</li><li><strong>Course 14: </strong>R Programming for Data Science</li><li><strong>Course 15: </strong>GDPR UK Training</li><li><strong>Course 16: </strong>Career Development Plan Fundamentals</li><li><strong>Course 17: </strong>CV Writing and Job Searching</li><li><strong>Course 18: </strong>Learn to Level Up Your Leadership</li><li><strong>Course 19: </strong>Networking Skills for Personal Success</li><li><strong>Course 20: </strong>Ace Your Presentations: Public Speaking Masterclass</li></ul><p><strong>What will make you stand out?</strong></p><p>Upon completion of this online Python, Data Science, Machine Learning, SQL, Cloud computing &amp; Cyber Security bundle, you will gain the following:</p><ul><li>CPD QS Accredited Proficiency with this Python &amp; Data Science bundle</li><li>After successfully completing the Python &amp; Data Science bundle, you will receive a FREE PDF Certificate from REED as evidence of your newly acquired abilities.</li><li>Lifetime access to the whole collection of learning materials of this Python &amp; Data Science bundle</li><li>The online test with immediate results</li><li>You can study and complete the Python &amp; Data Science bundle at your own pace.</li><li>Study for the Python &amp; Data Science bundle using any internet-connected device, such as a computer, tablet, or mobile device.</li></ul><p>Each course in this Python, Data Science, Machine Learning, SQL, Cloud computing &amp; Cyber Security bundle holds a prestigious CPD accreditation, symbolising exceptional quality. The materials, brimming with knowledge, are regularly updated, ensuring their relevance. This Python &amp; Data Science bundle promises not just education but an evolving learning experience. Engage with this extraordinary collection, and prepare to enrich your personal and professional development.</p><p>Embrace the future of learning with the Python, Data Science, Machine Learning, SQL, Cloud computing &amp; Cyber Security , a rich anthology of 30 diverse courses. Our experts handpick each course in the Python &amp; Data Science bundle to ensure a wide spectrum of learning opportunities. This Python &amp; Data Science bundle will take you on a unique and enriching educational journey.</p><p>The Python &amp; Data Science bundle encapsulates our mission to provide quality, accessible education for all. Whether you are just starting your career, looking to switch industries, or hoping to enhance your professional skill set, the Python &amp; Data Science bundle offers you the flexibility and convenience to learn at your own pace. Make the Python &amp; Data Science package your trusted companion in your lifelong learning journey.</p><h2>
        
        <div>CPD</div>
    </h2>

                        <div id="cpd">
                            <div>
                                <div>
                                    <div>
                                        200 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>The <strong>Python, Data Science, Machine Learning, SQL, Cloud computing &amp; Cyber Security  </strong>bundle is perfect for:</p><ul><li><strong>Beginners interested in technology: </strong>Individuals with little to no background in tech who are looking to start their careers in various IT domains.</li><li><strong>Aspiring Data Scientists and Analysts:</strong> Those aiming to build foundational and advanced skills in data science and machine learning.</li><li><strong>Future Software Developers: </strong>Individuals interested in learning Python and SQL for software development or database management.</li><li><strong>IT Security Enthusiasts: </strong>People who are keen on entering the field of cyber security and want to understand how to protect data in a digital environment.</li><li><strong>Cloud Computing Aspirants:</strong> Those looking to gain skills in cloud technologies and understand how to manage and deploy applications on the cloud.</li></ul>
                        </div><h2>
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                            <p>You are warmly invited to register for this Python, Data Science, Machine Learning, SQL, Cloud computing &amp; Cyber Security bundle. Please be aware that no formal entry requirements or qualifications are necessary. This curriculum has been crafted to be open to everyone, regardless of previous experience or educational attainment.</p>
                        </div><h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                            <p>Upon <strong>Python, Data Science, Machine Learning, SQL, Cloud computing &amp; Cyber Security  </strong>course completion, you can expect to:</p><ul><li>Python Developer</li><li>Data Analyst</li><li>Machine Learning Engineer</li><li>Database Administrator</li><li>Cloud Solutions Architect</li><li>Cyber Security Specialist</li><li>Data Science Consultant</li><li>Systems Analyst</li><li>Network Security Engineer</li><li>Research Scientist (AI/ML)</li></ul>
                        </div><h2>
        
        <div>Certificates</div>
    </h2>

                        <div id="optional_extras">
                                    <h4>20 CPD Quality Standard Pdf Certificates</h4>
        <p>
            Digital certificate -
            Included
        </p>

                        </div>

Compliance Central

Python, Data Science, Machine Learning, SQL, Cloud computing & Cyber Security

<p><strong>Python programmers</strong> are in great demand for a variety of reasons, including the language's widespread use and popularity as well as the fact that Python has emerged as a viable alternative in several fields. Developing web applications, working with data science, and machine learning can be done through Python codes. As a result, expertise in Python can open up a wide range of opportunities for you. If you want to develop your skills from scratch, or just want to refresh your old skills, we got you covered. We offer a <strong>Python Programming at QLS Level 7</strong> course discussing the basics to advanced techniques.</p><p><strong> Enrol this course and achieve the Quality Licence Scheme endorsed certificate </strong></p><p>Learners who are highly motivated and computer literate and who want to learn how to program in python should enrol in this course. It is great for developing your coding skills. We focused on a vast array of tools and technologies in this extensive course, including:</p><ul><li>Introduction to Python Programming from A-Z</li><li>Getting Familiar with Python</li><li>Basic Data Types</li><li>Python Operators</li><li>Advanced-Data Types</li><li>Control Flow Part 1</li><li>Control Flow Part 2</li><li>Functions</li><li>User Input and Error Handling</li><li>Python Advanced Functions</li><li>Python Scripting and Libraries</li><li>NumPy</li><li>Pandas</li><li>Introduction to OOP</li><li>Advanced OOP</li></ul><p>In the UK, there are more than <strong>750 new job posts for software engineers</strong> every day, and Python is the second-most in-demand programming language among companies. So, if you want to manage your future and make money by learning new skills, Python can be your best bet.</p><p>This course training includes 1 of the best-selling course endorsed by the Quality Licence Scheme with an endorsed certificate of achievement, expert assistance, and course assessment. Enjoy 12 months of free access to this course and master a range of in-demand professional skills to advance your career. <strong>No hidden costs - simply enrol this course.</strong></p><p><strong>Our course is endorsed by the Quality Licence Scheme, ensuring your newly acquired skills will enhance your professional development. This course is accredited by CPD.</strong></p><p>Dedicated learning assistance and 24/7 customer support are available to all students with this premium quality this course. Get the help you require and the answers to all your queries throughout the comprehensive syllabus of this course.</p><p>With this Python Programming at QLS Level 7 training, success becomes much easier and enables you to monetise your skills. This course is designed for both part-time and full-time students and can be completed at a pace that suits your learning style.</p><p><strong>Curriculum Breakdown:</strong></p><ul><li><strong>Module 01: Introduction to Python Programming from A-Z<br /></strong></li><li><strong>Module 02: Getting Familiar with Python<br /></strong></li><li><strong>Module 03: Basic Data Types<br /></strong></li><li><strong>Module 04: Python Operators<br /></strong></li><li><strong>Module 05: Advanced Data Types<br /></strong></li><li><strong>Module 06: Control Flow Part 1<br /></strong></li><li><strong>Module 07: Control Flow Part 2<br /></strong></li><li><strong>Module 08: Python Functions<br /></strong></li><li><strong>Module 09: User Input and Error Handling<br /></strong></li><li><strong>Module 10: Python Advanced Functions<br /></strong></li><li><strong>Module 11: Python Scripting and Libraries<br /></strong></li><li><strong>Module 12: NumPy<br /></strong></li><li><strong>Module 13: Pandas<br /></strong></li><li><strong>Module 14: Introduction to OOP<br /></strong></li><li><strong>Module 15: Advanced OOP<br /></strong></li><li><strong>Module 16: Starting a Career in Python</strong></li></ul><p><strong>Key Highlights</strong></p><ul><li>The Quality Licence Scheme ensures that the course you enrolled in, Python Programming at QLS Level 7, is of the highest quality.</li><li>It helps you to get recognised by employers easily.</li><li>The endorsed certificate of this course will make you stand out from the crowd when applying for jobs during this pandemic.</li><li>The Certificate of Achievement Endorsed by the Quality Licence Scheme has helped thousands of people reach their professional goals and get better jobs.</li></ul><p><strong>Why People Enrol from One Education:</strong></p><ul><li>Receive a Quality Licence Scheme-endorsed certificate upon successful completion of the course</li><li>Learning materials of the course contain engaging voiceover and visual elements for your comfort</li><li>Get 24/7 access to all course content for a full year</li><li>Each of our students gets full tutor support on weekdays (Monday to Friday)</li><li>Efficient assessments and instant results upon completion of the course</li></ul><p>This uniquely tailored course makes online learning as efficient and easy as possible. This this course will motivate you to learn, develop, and participate in an exceptional e-learning journey while upgrading your CV &amp; competence and introducing you to new possibilities to further your career development.</p><p><strong>Course Assessment</strong></p><p>You will immediately be given access to a specifically crafted MCQ test upon completing an online module. For each test, the pass mark will be set to 60%.</p><p><strong>Certificate of Achievement</strong></p><p><strong>QLS Endorsed Certificate </strong></p><p>After completing this course, learners will get an endorsed certificate (Completly FREE) delivered right at their doorstep by post, without paying a single penny! Please note that learners outside the UK must pay a £10 postage charge.</p><p><strong>Accredited Certificate </strong></p><p>After completing the MCQ assessment of this course, you will also qualify for a CPD QS Accredited Certificate from One Education as proof of your continued professional development. Certification is available in PDF format at the cost of £9, or a hard copy can be sent to you via post at the expense of £15.</p><h2>
        
        <div>Who is this course for?</div>
    </h2>

                        <div id="who_is_this_course_for">
                            <p>This course is ideal for highly motivated individuals or teams who want to enhance their professional skills and efficiently skilled employees.</p>
                        </div><h2>
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                            <p>There are no formal entry requirements for this course, with enrollment open to anyone!</p>
                        </div><h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                            <p>This course can help you to develop your career by helping you to apply for high-paying employment in the related fields.<br />Enrol now and take your career to the next step.</p>
                        </div>

One Education

Python Programming at QLS Level 7 Course

<p dir="ltr" id="isPasted" fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><span style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="color:#000000;">Python for Data Science and Machine Learning Bootcamp course is a comprehensive and practical online course designed to teach you how to use Python for data science and machine learning.&nbsp;</span></p><p dir="ltr" fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><span style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="color:#000000;">The course comprises several sections, each covering different topics in data science and machine learning. It includes all the essential concepts and tools required to analyse and manipulate data, build machine learning models, and make predictions or decisions.</span></p><p dir="ltr" fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><span style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="color:#000000;">It also covers dataset summary statistics and visualisation techniques using libraries like matplotlib and seaborn. You&#39;ll learn about model selection, ensemble approaches, and parameter adjustment. Additionally, you will discover how to export and load machine learning models using libraries such as pickle and joblib.</span></p><p dir="ltr" fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><span style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="color:#000000;">This course is suitable for anyone interested in learning Python for data science and machine learning. Whether you are an aspiring data scientist or a professional looking to enhance your data analysis skills, this course will help you achieve your goals.</span></p><p dir="ltr" fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><span style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="color:#000000;">Enrol now to gain instant access to the course materials and start your learning journey. Don&#39;t miss out on the opportunity to acquire one of the most in-demand skills in the market today and become a proficient data scientist and machine learning expert.</span></p><h2 dir="ltr" id="isPasted" fr-original-style="" style="box-sizing: border-box;"><span style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="color:#000000;">Learning Outcome of Python for Data Science and Machine Learning Bootcamp &nbsp; &nbsp;</span></h2><ul fr-original-style="" style="box-sizing: border-box;"><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Master fundamental concepts of machine learning and its applications.</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Gain proficiency in Python programming for data analysis and manipulation.</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Learn to load, read, and manipulate CSV data files using Python libraries.</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Understand dataset summary statistics and visualization techniques.</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Acquire skills in data preparation and preprocessing.</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Explore feature selection techniques and their importance.</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Evaluate machine learning algorithms using various techniques and metrics.</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Spot check classification and regression algorithms for model selection.</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Improve model performance using ensemble methods and parameter tuning.</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Learn to export, save, load, and finalize machine learning models for real-time predictions.</li></ul><h2 dir="ltr" fr-original-style="" style="box-sizing: border-box;"><span style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="color:#000000;">Key Features of the Course</span></h2><ul fr-original-style="" style="box-sizing: border-box;"><li dir="ltr" style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">A CPD certificate that is recognised worldwide.</li><li dir="ltr" style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">A great online learning experience.</li><li dir="ltr" style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Interesting and unique online materials and activities.</li><li dir="ltr" style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Expert guidance and support from the field leaders.</li><li dir="ltr" style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Access to the study resources anytime you want.</li><li dir="ltr" style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Friendly and helpful customer service and admin support by email, phone, and chat from Monday through Friday.</li><li dir="ltr" style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Get a year-long access to the course.</li></ul><h2 dir="ltr" fr-original-style="" style="box-sizing: border-box;"><span style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="color:#000000;">Who is this course for</span></h2><p dir="ltr" fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><span style="color: rgb(0, 0, 0); font-size: 16px; box-sizing: border-box;" fr-original-style="color: rgb(0, 0, 0); font-size: 16px;">This Python for Data Science and Machine Learning Bootcamp Course is suitable for -</span></p><ul fr-original-style="" style="box-sizing: border-box;"><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Aspiring data scientists and machine learning enthusiasts</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Professionals seeking to enhance their data analysis skills</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Individuals interested in Python programming for data science</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Anyone looking to break into the field of data science and machine learning</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Students pursuing studies in computer science or related fields</li></ul><h2 dir="ltr" fr-original-style="" style="box-sizing: border-box;"><span style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="color:#000000;">Requirements</span></h2><ul fr-original-style="" style="box-sizing: border-box;"><li id="isPasted" style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Basic understanding of programming concepts</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Familiarity with Python programming language is beneficial but not mandatory</li><li dir="ltr" style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">No prerequisites; suitable for individuals from any academic background.</li><li dir="ltr" style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Accessible course materials from any internet-enabled device.</li></ul><h2 dir="ltr" fr-original-style="" style="box-sizing: border-box;"><span style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="color:#000000;">CPD Certificate from Course Gate</span></h2><p dir="ltr" fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><span style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="color:#000000;">At the successful completion of the course, you can obtain your CPD certificate from us. You can order the PDF certificate for &pound;9 and the hard copy for &pound;15. Also, you can order both PDF and hardcopy certificates for &pound;22.</span></p><h2 dir="ltr" fr-original-style="" style="box-sizing: border-box;"><span style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="color:#000000;">Career path</span><span style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="color: rgb(0, 0, 0);"><br fr-original-style="" style="box-sizing: border-box;"></span></h2><div style="color: rgb(68, 68, 68); box-sizing: border-box;" id="isPasted" fr-original-style=" color: rgb(68, 68, 68);"><div style="color: rgb(68, 68, 68); box-sizing: border-box;" fr-original-style=" color: rgb(68, 68, 68);"><div data-elementor-type="wp-post" data-elementor-id="357815" data-elementor-post-type="course" fr-original-style="" style="box-sizing: border-box;"><section data-id="5767f71a" data-element_type="section" fr-original-style="" style="box-sizing: border-box;"><div data-id="58784751" data-element_type="column" fr-original-style="" style="box-sizing: border-box;"><div data-id="ce105db" data-element_type="widget" data-widget_type="text-editor.default" style="color: var( --e-global-color-text ); box-sizing: border-box;" fr-original-style=" color: var( --e-global-color-text );"><ul fr-original-style="" style="box-sizing: border-box;"><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Data Scientist</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Data Analyst</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Machine Learning Engineer</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Business Intelligence Analyst</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Data Engineer</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Research Scientist</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Quantitative Analyst</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Artificial Intelligence Specialist</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Data Consultant</li><li style="font-size: 16px; color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="font-size: 16px; color: rgb(0, 0, 0);">Statistician</li></ul></div></div></section></div></div></div>

Course Gate

Python for Data Science and Machine Learning Bootcamp online course is suitable for anyone interested in learning Python for data science and machine learning. It is especially ideal for aspiring data scientists and professionals seeking to enhance their data analysis skills. 

Python for Data Science and Machine Learning Bootcamp

<h2 style="color: var(--text-heading); box-sizing: border-box;" id="isPasted" fr-original-style="color: var(--text-heading);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><span style="font-size: 24px; box-sizing: border-box;" fr-original-style="font-size: 24px;">This course at a glance</span></strong></h2><ul style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="color: rgb(0, 0, 0);"><li style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="color: rgb(0, 0, 0);">Accredited by CPDQE</li><li id="isPasted" fr-original-style="" style="box-sizing: border-box;"><span style="color: rgb(38, 99, 82) !important; box-sizing: border-box;" fr-original-style=" color: rgb(38, 99, 82) !important;">Learn how to become a data scientist, data engineer, data analyst or consultant</span></li><li fr-original-style="" style="box-sizing: border-box;"><span style="color: rgb(38, 99, 82) !important; box-sizing: border-box;" fr-original-style=" color: rgb(38, 99, 82) !important;">Know the different processes of Data Science, such as data cleaning, processing, wrangling, manipulation</span></li><li fr-original-style="" style="box-sizing: border-box;"><span style="color: rgb(38, 99, 82) !important; box-sizing: border-box;" fr-original-style=" color: rgb(38, 99, 82) !important;">Discover the usage of R to clean, analyse, and visualise data</span></li><li fr-original-style="" style="box-sizing: border-box;"><span style="color: rgb(38, 99, 82) !important; box-sizing: border-box;" fr-original-style=" color: rgb(38, 99, 82) !important;">How to write complex R programs for real-life industry situations</span></li><li fr-original-style="" style="box-sizing: border-box;"><span style="color: rgb(38, 99, 82) !important; box-sizing: border-box;" fr-original-style=" color: rgb(38, 99, 82) !important;">Get data scientist resume tips and land your first job</span></li><li fr-original-style="" style="box-sizing: border-box;"><span style="color: rgb(38, 99, 82) !important; box-sizing: border-box;" fr-original-style=" color: rgb(38, 99, 82) !important;">Explore the various applications of Machine Learning</span></li><li fr-original-style="" style="box-sizing: border-box;"><span style="color: rgb(38, 99, 82) !important; box-sizing: border-box;" fr-original-style=" color: rgb(38, 99, 82) !important;">Understand Tidyverse, Operators, Vectors, Lists and their applications</span></li><li fr-original-style="" style="box-sizing: border-box;"><span style="color: rgb(38, 99, 82) !important; box-sizing: border-box;" fr-original-style=" color: rgb(38, 99, 82) !important;">Uncover data extraction and scraping</span></li></ul><p style="color: rgb(38, 99, 82) !important; font-size: var(--font-size); box-sizing: border-box;" id="isPasted" fr-original-style=" color: rgb(38, 99, 82) !important;">Data science and Machine Learning are one of the most popular fields in the world today. Data science is crucial to analysing and developing data-based machine learning models. We will cover programming in R in this course for data science and machine learning.</p><p style="color: rgb(38, 99, 82) !important; font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(38, 99, 82) !important;">R programming is a specialised skill that is in high demand today. We&rsquo;ve designed our&nbsp;<b fr-original-style="" style="box-sizing: border-box;">Data Science and Machine Learning with R</b>&nbsp;course to help you learn fundamentals through advanced R programming. This course teaches you how to effectively use R programming for machine learning or data science. You&rsquo;ll learn how to visualise data by plotting in R, as well as how to clean data.&nbsp;</p><p style="color: rgb(38, 99, 82) !important; font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(38, 99, 82) !important;">You will receive training in machine learning and its many real-world applications while working with R Shiny to create web applications and online interactive dashboards. In other words, you will gain practical, step-by-step knowledge of the R programming language that you may use for business or professional purposes.</p><p style="color: rgb(38, 99, 82) !important; font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(38, 99, 82) !important;">An expert instructor designed this&nbsp;<b fr-original-style="" style="box-sizing: border-box;">&ldquo;Data Science and Machine Learning with R&rdquo;</b>&nbsp;course to provide you with the best learning experience possible. Our goal is for you to learn and apply the lessons from this course to improve your skills.&nbsp;</p><p style="color: rgb(38, 99, 82) !important; font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(38, 99, 82) !important;">To explore the world of R Programming Language, Enrol Now!</p><h3 style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);"><span style="font-size: 24px; box-sizing: border-box;" fr-original-style="font-size: 24px;">Accredited by</span></h3><p style="color: rgb(15, 21, 26); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(15, 21, 26);">This course is <strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">CPDQE&nbsp;</strong>accredited, which serves as an impactful mechanism for skill enhancement.&nbsp;</p><p style="color: rgb(0, 0, 0); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);">Continuing Professional Development (CPD) stands as a crucial, widely acknowledged method that aids individuals, organisations, and entire industries in staying current with their skills and knowledge.</p><p style="color: rgb(0, 0, 0); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);">CPD not only facilitates the elevation of global standards and benchmarks, aligning with the growing forces of globalisation and consumer expectations but also transforms learning into a deliberate and proactive process. It motivates professionals to uphold a consistently high level of performance and demonstrates their unwavering commitment to a specific job role or profession.</p><p style="color: rgb(0, 0, 0); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><span style="font-size: 24px; box-sizing: border-box;" fr-original-style="font-size: 24px;">Course Curriculum</span></strong></p><ul fr-original-style="" style="box-sizing: border-box;"><li id="isPasted" fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Introduction to Data Science +ML with R from A-Z</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Getting Started with R</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Data Types and Structures in R</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Intermediate R</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Data Manipulation in R</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Data Visualization in R</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Creating Reports with R Markdown</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Building Webapps with R Shiny</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Introduction to Machine Learning</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Data Preprocessing</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Linear Regression: A Simple Model</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Exploratory Data Analysis</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Linear Regression: A Real Model</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Logistic Regression</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Starting a Career in Data Science</strong></li></ul>

LearnDrive UK

The course covers data science and machine learning with R.



Data Science and Machine Learning with R

<strong>This course starts with the basics of data science and gradually moves towards explaining the concepts of machine learning and various data science algorithms.</strong>
        <p>Machine learning is the key to development in many areas, such as IT, security, marketing, automation, and even medicine. Without machine learning, it is impossible to build intelligent applications and devices, such as Alexa, Siri, and Google Assistant. This course will help to get familiar with data science and machine learning.

The course starts with an introduction to data science, explaining different terms associated with it. You will also become familiar with machine learning and data science modeling and explore the key differences between model parameters and hyperparameters. Next, you will become familiar with the concepts of machine learning models, such as linear regression, decision trees, random forests, neural networks, and clustering techniques. Towards the end, you will learn how to evaluate machine learning models and learn the best practices to succeed in your data scientist role.

By the end of this course, you will have a solid understanding of data science and machine learning fundamentals.</p>
        <h2>What You Will Learn</h2><p>Become familiar with data science and machine learning terms<br>Distinguish between model parameters and hyperparameters<br>Distinguish between supervised and unsupervised learning<br>Discover how decision trees, bagging, and random forest works<br>Understand the importance of the k-nearest neighbors (KNN) algorithm in machine learning<br>Learn about neural networks and clustering techniques<br>Evaluate the performance of machine learning models</p>
        <h2>Audience</h2><p>This course is designed for students and beginners who want to understand the concepts, statistics, and math behind machine learning algorithms and for those who are curious to solve real-world problems using machine learning and data science. Everything is taught from scratch; hence, there are no prerequisites to get started with this course.</p>
        <h2>Approach</h2><p>With the help of simple explanation, avoiding confusing mathematical notation and jargon, this course covers the fundamentals of data science, machine learning, and data mining from scratch.</p>
        <h2>Key Features</h2><p>Learn the fundamentals of data science, machine learning, and data mining * Learn interesting techniques to evaluate a machine learning model * Discover the best practices to solve real-world problems using machine learning</p>
        
        <h2>About the Author</h2><h3>AI Sciences</h3><p>AI Sciences are experts, PhDs, and artificial intelligence practitioners, including computer science, machine learning, and Statistics. Some work in big companies such as Amazon, Google, Facebook, Microsoft, KPMG, BCG, and IBM.

AI sciences produce a series of courses dedicated to beginners and newcomers on techniques and methods of machine learning, statistics, artificial intelligence, and data science. They aim to help those who wish to understand techniques more easily and start with less theory and less extended reading. Today, they publish more comprehensive courses on specific topics for wider audiences.

Their courses have successfully helped more than 100,000 students master AI and data science.</p>
        <h2>Course Outline</h2><h4>1. Welcome and Introduction</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Welcome</p><p style='margin: 0'>This video welcomes you to the course.</p></td></tr><tr><td style='padding: 15px;'><p>2. Introduction to Data Science</p><p style='margin: 0'>This video provides an introduction to data science.</p></td></tr></tbody></table><br><h4>2. Preliminary Requirements to Understand Data Science and Machine Learning</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Understanding Data Science Terms</p><p style='margin: 0'>This video provides an overview of the terms used in data science.</p></td></tr><tr><td style='padding: 15px;'><p>2. Understanding Machine Learning</p><p style='margin: 0'>This video presents an overview of machine learning.</p></td></tr><tr><td style='padding: 15px;'><p>3. Types of Learning</p><p style='margin: 0'>This video explains the different types of learning.</p></td></tr><tr><td style='padding: 15px;'><p>4. Understanding Data Science Modeling</p><p style='margin: 0'>This video focuses on data science modeling.</p></td></tr><tr><td style='padding: 15px;'><p>5. Model parameters versus Hyperparameters</p><p style='margin: 0'>This video explains the difference between model parameters and hyperparameters.</p></td></tr></tbody></table><br><h4>3. Machine Learning Models</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. How Linear Regression Works</p><p style='margin: 0'>This video demonstrates how linear regression works.</p></td></tr><tr><td style='padding: 15px;'><p>2. How Decision Trees Work</p><p style='margin: 0'>This video demonstrates how decision trees work.</p></td></tr><tr><td style='padding: 15px;'><p>3. How Bagging and Random Forest Work</p><p style='margin: 0'>This video demonstrates the working of bagging and random forest.</p></td></tr><tr><td style='padding: 15px;'><p>4. How Support Vector Machine Works</p><p style='margin: 0'>This video demonstrates the working of support vector machines.</p></td></tr><tr><td style='padding: 15px;'><p>5. Neural Networks- Part 1</p><p style='margin: 0'>This video is the first part of a two-part video that explains neural networks.</p></td></tr><tr><td style='padding: 15px;'><p>6. Neural Networks- Part 2</p><p style='margin: 0'>This is the second part of the two-part video that explains neural networks.</p></td></tr><tr><td style='padding: 15px;'><p>7. How Logistic Regression Works</p><p style='margin: 0'>This video demonstrates the working of logistic regression.</p></td></tr><tr><td style='padding: 15px;'><p>8. How k-nearest neighbour (KNN) Works</p><p style='margin: 0'>This video focuses on KNN and explains how it works.</p></td></tr><tr><td style='padding: 15px;'><p>9. Clustering Techniques</p><p style='margin: 0'>This video explains the different clustering techniques.</p></td></tr></tbody></table><br><h4>4. Model Performance</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Evaluating Models Performance</p><p style='margin: 0'>This video demonstrates how to evaluate the performance of the models.</p></td></tr></tbody></table><br><h4>5. Best Practices for a Data Scientist</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Best Practices for a Data Scientist</p><p style='margin: 0'>This video explains the best practices used by data scientists.</p></td></tr></tbody></table>

Algorithms

This course starts with the basics of data science and gradually moves towards explaining the concepts of machine learning and various data science algorithms.

Mastering Data Science and Machine Learning Fundamentals

<p>Feeling Stuck in Your Career? The Python for Data Science and Machine Learning-(30 in 1) CPD Accredited Courses! Bundle is Your Skill-Building Solution. This exceptional collection of <strong>30 premium courses</strong> is designed to encourage growth and improve your career opportunities. Suited to meet different interests and goals, the  Python for Data Science and Machine Learning bundle provides an engaging learning experience, helping you learn skills across various disciplines.</p><p>With Python for Data Science and Machine Learning-(30 in 1) CPD Accredited Courses! Bundle, you'll have a personalised journey that aligns with your career goals and interests. This comprehensive package helps you confidently tackle new challenges, whether entering a new field or enhancing your existing knowledge. The  Python for Data Science and Machine Learning bundle is your gateway to expanding your career options, increasing job demand, and enhancing your skill set.</p><p>By enrolling in this bundle, you'll receive complimentary PDF certificates for all courses, adding value to your resume at no extra cost. Develop key skills and achieve important progress in your career and personal development. Start your journey today and experience the transformative impact of the Python for Data Science and Machine Learning-(30 in 1) CPD Accredited Courses! bundle on your job life and career growth!</p><p><strong>This Python for Data Science and Machine Learning-(30 in 1) CPD Accredited Courses! Bundle Comprises the Following CPD Accredited Courses:</strong></p><ul><li><strong>Course 01</strong>: Machine Learning Basics</li><li><strong>Course 02</strong>: Azure Machine Learning</li><li><strong>Course 03</strong>: Python Intermediate Training</li><li><strong>Course 04</strong>: Python Data Science</li><li><strong>Course 05</strong>: 2021 Data Science &amp; Machine Learning with R from A-Z</li><li><strong>Course 06</strong>: Complete Python Machine Learning &amp; Data Science Fundamentals</li><li><strong>Course 07</strong>: Learn Python, JavaScript, and Microsoft SQL for Data science</li><li><strong>Course 08</strong>: Spatial Data Visualisation and Machine Learning in Python</li><li><strong>Course 09</strong>: Complete Python Machine Learning &amp; Data Science Fundamentals</li><li><strong>Course 10</strong>: Python Programming Bible | Networking, GUI, Email, XML, CGI</li><li><strong>Course 11</strong>: Deep Learning &amp; Neural Networks Python - Keras</li><li><strong>Course 12</strong>: The Complete Python 3 Course: Beginner to Advanced!</li><li><strong>Course 13</strong>: Building Big Data Pipelines with PySpark MongoDB and Bokeh</li><li><strong>Course 14</strong>: Clinical Data Management with SAS Programming</li><li><strong>Course 15</strong>: Certificate in Data Entry and Management</li><li><strong>Course 16</strong>: Quick Data Science Approach from Scratch</li><li><strong>Course 17</strong>: SQL for Data Science, Data Analytics and Data Visualization</li><li><strong>Course 18</strong>: Programming AutoCAD with SQL Server Database Using C#</li><li><strong>Course 19</strong>: Big Data Analytics with PySpark Power BI and MongoDB</li><li><strong>Course 20</strong>: Develop Big Data Pipelines with R &amp; Sparklyr &amp; Tableau</li><li><strong>Course 21</strong>: Develop Big Data Pipelines with R, Sparklyr &amp; Power BI</li><li><strong>Course 22</strong>: Data Center Training Essentials: Power &amp; Electrical</li><li><strong>Course 23</strong>: Business Intelligence and Data Mining</li><li><strong>Course 24</strong>: Data Analysis In Excel</li><li><strong>Course 25</strong>: CV Writing and Job Searching</li><li><strong>Course 26</strong>: Learn to Level Up Your Leadership</li><li><strong>Course 27</strong>: Networking Skills for Personal Success</li><li><strong>Course 28</strong>: Ace Your Presentations: Public Speaking Masterclass</li><li><strong>Course 29</strong>: Learn to Make a Fresh Start in Your Life</li><li><strong>Course 30</strong>: Motivation - Motivating Yourself &amp; Others</li></ul><p><strong>What will make you stand out?</strong></p><p>Upon completion of this online Python for Data Science and Machine Learning-(30 in 1) CPD Accredited Courses! Bundle, you will gain the following:</p><ul><li>CPD QS Accredited Proficiency with this  Python for Data Science and Machine Learning  Bundle </li><li>After successfully completing the  Python for Data Science and Machine Learning bundle, you will receive a FREE PDF Certificate from REED as evidence of your newly acquired abilities.</li><li>Lifetime access to the whole collection of learning materials of this  Python for Data Science and Machine Learning       Bundle</li><li>The online test with immediate results </li><li>You can study and complete the  Python for Data Science and Machine Learning bundle at your own pace.</li><li>Study for the  Python for Data Science and Machine Learning bundle using any internet-connected device, such as a computer, tablet, or mobile device.</li></ul><p>The  Python for Data Science and Machine Learning-(30 in 1) CPD Accredited Courses! bundle is a premier learning resource, with each course module holding respected CPD accreditation, symbolising exceptional quality. The content is packed with knowledge and is regularly updated to ensure it remains relevant. This bundle offers not just education but a constantly improving learning experience designed to enrich both your personal and professional development.</p><p>Advance the future of learning with the   Python for Data Science and Machine Learning bundle, a comprehensive, complete collection of 30 courses. Each course in the  Python for Data Science and Machine Learning bundle has been handpicked by our experts to provide a broad range of learning opportunities. Together, these modules form an important and well-rounded learning experience.</p><p>Our mission is to deliver high-quality, accessible education for everyone. Whether you are starting your career, switching industries, or enhancing your professional skills, the   Python for Data Science and Machine Learning bundle offers the flexibility and convenience to learn at your own pace. Make the   Python for Data Science and Machine Learning package your trusted partner in your lifelong learning journey.</p><h2>
        
        <div>CPD</div>
    </h2>

                        <div id="cpd">
                            <div>
                                <div>
                                    <div>
                                        300 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>The Python for Data Science and Machine Learning-(30 in 1) CPD Accredited Courses! is perfect for:</p><ul><li>Expand your knowledge and skillset for a fulfilling career with the  Python for Data Science and Machine Learning bundle.</li><li>Become a more valuable professional by earning CPD certification and mastering in-demand skills with the  Python for Data Science and Machine Learning bundle.</li><li>Discover your passion or explore new career options with the diverse learning opportunities in the  Python for Data Science and Machine Learning bundle.</li><li>Learn on your schedule, in the comfort of your home - the  Python for Data Science and Machine Learning bundle offers ultimate flexibility for busy individuals.</li></ul>
                        </div><h2>
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                            <p>You are warmly invited to register for this bundle. Please be aware that no formal entry requirements or qualifications are necessary. This curriculum has been crafted to be open to everyone, regardless of previous experience or educational attainment.</p>
                        </div><h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                            <p>Gain a wide range of skills across various fields, improve your problem-solving capabilities, and keep current with industry trends. Perfect for those aiming for career advancement, exploring a new professional direction, or pursuing personal growth. Begin your journey with the  Python for Data Science and Machine Learning bundle.</p>
                        </div><h2>
        
        <div>Certificates</div>
    </h2>

                        <div id="optional_extras">
                                    <h4>CPD Certificates</h4>
        <p>
            Digital certificate -
            Included
        </p>

                        </div>

Python for Data Science and Machine Learning-(30 in 1) CPD Accredited Courses!

<h2 style="color: var(--text-heading); box-sizing: border-box;" id="isPasted" fr-original-style="color: var(--text-heading);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><span style="font-size: 24px; box-sizing: border-box;" fr-original-style="font-size: 24px;">This course at a glance</span></strong></h2><ul style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="color: rgb(0, 0, 0);"><li style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="color: rgb(0, 0, 0);">Accredited by CPDQE</li><li id="isPasted" fr-original-style="" style="box-sizing: border-box;"><span style="color: rgb(38, 99, 82) !important; box-sizing: border-box;" fr-original-style=" color: rgb(38, 99, 82) !important;">Learn how to clean, process, wrangle, and manipulate data</span></li><li fr-original-style="" style="box-sizing: border-box;"><span style="color: rgb(38, 99, 82) !important; box-sizing: border-box;" fr-original-style=" color: rgb(38, 99, 82) !important;">Know how to create a resume for a data science job</span></li><li fr-original-style="" style="box-sizing: border-box;"><span style="color: rgb(38, 99, 82) !important; box-sizing: border-box;" fr-original-style=" color: rgb(38, 99, 82) !important;">Get a grasp of NumPy by learning how to use it for numerical data</span></li><li fr-original-style="" style="box-sizing: border-box;"><span style="color: rgb(38, 99, 82) !important; box-sizing: border-box;" fr-original-style=" color: rgb(38, 99, 82) !important;">Uncover the secret of different Python libraries, such as Pandas, Matplotlib, SciPy and many more</span></li><li fr-original-style="" style="box-sizing: border-box;"><span style="color: rgb(38, 99, 82) !important; box-sizing: border-box;" fr-original-style=" color: rgb(38, 99, 82) !important;">Explore machine learning concepts and algorithms</span></li><li fr-original-style="" style="box-sizing: border-box;"><span style="color: rgb(38, 99, 82) !important; box-sizing: border-box;" fr-original-style=" color: rgb(38, 99, 82) !important;">Discover developing custom data solutions</span></li></ul><p style="color: rgb(38, 99, 82) !important; font-size: var(--font-size); box-sizing: border-box;" id="isPasted" fr-original-style=" color: rgb(38, 99, 82) !important;">You can create various applications for science, math, machine learning, and data science with Python. As a high-level, general-purpose programming language, Python is quite English-like and easy to learn. This&nbsp;<b fr-original-style="" style="box-sizing: border-box;">Python for Data Science and Machine Learning</b>&nbsp;course will show you how to use Python for machine learning and data science.</p><p style="color: rgb(38, 99, 82) !important; font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(38, 99, 82) !important;">During the course, you will master every useful Python skill you need for data science and machine learning. If you find it challenging to write complex Python programs, we&rsquo;ll show you how to do so with our step-by-step instructions based on actual work contexts. You&rsquo;ll also learn how to run the regression, classification, and clustering and the specifics of supervised and unsupervised machine learning. Moreover, this course covers how statistics work for data science, hypothesis testing, and much more.</p><p style="color: rgb(38, 99, 82) !important; font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(38, 99, 82) !important;">An expert instructor designed this&nbsp;<b fr-original-style="" style="box-sizing: border-box;">&ldquo;Python for Data Science and Machine Learning&rdquo;</b>&nbsp;course to provide you with the best learning experience possible. Our goal is for you to learn and apply the lessons from this course to improve your skills.&nbsp;</p><p style="color: rgb(38, 99, 82) !important; font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(38, 99, 82) !important;">To become a master of Python, Enrol Now!</p><h3 style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);"><span style="font-size: 24px; box-sizing: border-box;" fr-original-style="font-size: 24px;">Accredited by</span></h3><p style="color: rgb(15, 21, 26); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(15, 21, 26);">This course is <strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">CPDQE&nbsp;</strong>accredited, which serves as an impactful mechanism for skill enhancement.&nbsp;</p><p style="color: rgb(0, 0, 0); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);">Continuing Professional Development (CPD) stands as a crucial, widely acknowledged method that aids individuals, organisations, and entire industries in staying current with their skills and knowledge.</p><p style="color: rgb(0, 0, 0); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);">CPD not only facilitates the elevation of global standards and benchmarks, aligning with the growing forces of globalisation and consumer expectations but also transforms learning into a deliberate and proactive process. It motivates professionals to uphold a consistently high level of performance and demonstrates their unwavering commitment to a specific job role or profession.</p><p style="color: rgb(0, 0, 0); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);"><br fr-original-style="" style="box-sizing: border-box;"></p><p style="color: rgb(0, 0, 0); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><span style="font-size: 24px; box-sizing: border-box;" fr-original-style="font-size: 24px;">Course Curriculum</span></strong></p><ul fr-original-style="" style="box-sizing: border-box;"><li id="isPasted" fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Introduction to Python for Data Science &amp; Machine Learning from A-Z</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Data Science &amp; Machine Learning Concepts</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Python For Data Science</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Statistics for Data Science</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Probability and Hypothesis Testing</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">NumPy Data Analysis</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Pandas Data Analysis</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Python Data Visualization</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Introduction to Machine Learning</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Data Loading &amp; Exploration</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Data Cleaning</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Feature Selecting and Engineering</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Linear and Logistic Regression</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">K Nearest Neighbours</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Decision Trees</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Ensemble Learning and Random Forests</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Support Vector Machines</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">K-Means</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">PCA</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Data Science Career</strong></li></ul>

This course aims to teach you how to use Python for machine learning and data science.



Python for Data Science and Machine Learning

<strong>In this practical, hands-on course, you'll learn how to use R for effective data analysis and visualization and how to make use of that data in a practical manner. You will learn how to install and configure software necessary for a statistical programming environment and describe generic programming language concepts as they are implemented in a high-level statistical language.</strong>
        <p>The course covers practical issues in statistical computing that include programming in R, reading data into R, accessing R packages, writing R functions, debugging, profiling R code, and organizing and commenting on R code. Blending practical work with solid theoretical training, we take you from the basics of R programming to mastery.

We understand that theory is important to build a solid foundation, we also understand that theory alone isn't going to get the job done so that's why this course is packed with practical hands-on examples that you can follow step by step. Even if you already have some coding experience, or want to learn about the advanced features of the R programming language, this course is for you!

R coding experience is either required or recommended in job postings for data scientists, machine learning engineers, big data engineers, IT specialists, database developers, and much more. Adding R coding language skills to your resume will help you in any one of these data specializations requiring mastery of statistical techniques.

By the end of the course, you'll be a professional data scientist with R and confidently apply for jobs and will feel good knowing that you have the skills and knowledge to back it up.

All resources are placed here: https://github.com/PacktPublishing/Data-Science-and-Machine-Learning-with-R-from-A-Z-Course-Updated-for-2021-</p>
        <h2>What You Will Learn</h2><p>Learn data cleaning, processing, wrangling, and manipulation<br>Learn plotting in R (graphs, charts, plots, histograms, and more)<br>How to create a resume and land your first job as a data scientist<br>Learn machine learning and its various practical applications<br>Learn data and file management in R<br>Use R to clean, analyze, and visualize data</p>
        <h2>Audience</h2><p>This course is designed for beginners who want to learn about data science and machine learning. No prior knowledge of R is required.</p>
        <h2>Approach</h2><p>This course takes you through data analysis in R, data visualization in R, and machine learning with hands-on step-by-step training.</p>
        <h2>Key Features</h2><p>Learn data extraction and web scraping * Learn to build custom data solutions * Learn automating dynamic report generation</p>
        <h2>Github Repo</h2><p>https://github.com/PacktPublishing/Data-Science-and-Machine-Learning-with-R-from-A-Z-Course-Updated-for-2021-</p>
        <h2>About the Author</h2><h3>Juan E. Galvan</h3><p>Juan E. Galvan has been an entrepreneur since grade school. His background is in the tech space from digital marketing, e-commerce, web development to programming. He believes in continuous education with the best of a university degree without all the downsides of burdensome costs and inefficient methods. He looks forward to helping people expand their skillsets.</p>
        <h2>Course Outline</h2><h4>1. Data Science and Machine Leaning Course Introduction</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Data Science and Machine Learning Introduction Section Overview</p><p style='margin: 0'>This video explains data science and machine learning.</p></td></tr><tr><td style='padding: 15px;'><p>2. What is Data Science?</p><p style='margin: 0'>This video explains the concept of data science.</p></td></tr><tr><td style='padding: 15px;'><p>3. Machine Learning Overview</p><p style='margin: 0'>This video gives an overview of machine learning.</p></td></tr><tr><td style='padding: 15px;'><p>4. Data Science + Machine Learning Marketplace</p><p style='margin: 0'>This video explains the various trends and job opportunities in data science and machine learning.</p></td></tr><tr><td style='padding: 15px;'><p>5. Who is this Course For?</p><p style='margin: 0'>This video explains the audience for this course.</p></td></tr><tr><td style='padding: 15px;'><p>6. Data Science and Machine Learning Job Opportunities</p><p style='margin: 0'>This video explains the various job opportunities in data science and machine learning.</p></td></tr><tr><td style='padding: 15px;'><p>7. Data Science Job Roles</p><p style='margin: 0'>This video explains the various job roles for data science.</p></td></tr></tbody></table><br><h4>2. Getting Started with R</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Getting Started with R</p><p style='margin: 0'>This video explains the concept of R.</p></td></tr><tr><td style='padding: 15px;'><p>2. R Basics</p><p style='margin: 0'>This video explains the R basics.</p></td></tr><tr><td style='padding: 15px;'><p>3. Working with Files</p><p style='margin: 0'>This video explains working with files in R.</p></td></tr><tr><td style='padding: 15px;'><p>4. R Studio</p><p style='margin: 0'>This video explains R studio.</p></td></tr><tr><td style='padding: 15px;'><p>5. Tidyverse Overview</p><p style='margin: 0'>This video provides an overview of tidyverse.</p></td></tr><tr><td style='padding: 15px;'><p>6. Additional Resources</p><p style='margin: 0'>This video shares some additional resources that will help you get along with the course.</p></td></tr></tbody></table><br><h4>3. Data Types and Structures in R</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Data Types and Structures in R Section Overview</p><p style='margin: 0'>This video explains data types and structures in R.</p></td></tr><tr><td style='padding: 15px;'><p>2. Basic Types</p><p style='margin: 0'>This video explains basic types in R.</p></td></tr><tr><td style='padding: 15px;'><p>3. Vectors - Part One</p><p style='margin: 0'>This video introduces you to vectors.</p></td></tr><tr><td style='padding: 15px;'><p>4. Vectors - Part Two</p><p style='margin: 0'>This video explains how to interact with R using vectors.</p></td></tr><tr><td style='padding: 15px;'><p>5. Vectors: Missing Values</p><p style='margin: 0'>This video explains vector missing values.</p></td></tr><tr><td style='padding: 15px;'><p>6. Vectors: Coercion</p><p style='margin: 0'>This video explains coercion.</p></td></tr><tr><td style='padding: 15px;'><p>7. Vectors: Naming</p><p style='margin: 0'>This video explains vector naming.</p></td></tr><tr><td style='padding: 15px;'><p>8. Vectors: Miscellaneous</p><p style='margin: 0'>This video explains miscellaneous yet important concepts in vectors.</p></td></tr><tr><td style='padding: 15px;'><p>9. Working with Matrices</p><p style='margin: 0'>This video explains working with matrices.</p></td></tr><tr><td style='padding: 15px;'><p>10. Working with Lists</p><p style='margin: 0'>This video explains working with lists.</p></td></tr><tr><td style='padding: 15px;'><p>11. Introduction to Data Frames</p><p style='margin: 0'>This video explains introduction to data frames.</p></td></tr><tr><td style='padding: 15px;'><p>12. Creating Data Frames</p><p style='margin: 0'>This video explains creating data frames.</p></td></tr><tr><td style='padding: 15px;'><p>13. Data Frames: Helper Functions</p><p style='margin: 0'>This video explains data frames helper functions.</p></td></tr><tr><td style='padding: 15px;'><p>14. Data Frames: Tibbles</p><p style='margin: 0'>This video explains Tibbles in data frames.</p></td></tr></tbody></table><br><h4>4. Intermediate R</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Intermedia R Section Introduction</p><p style='margin: 0'>This video introduces you to R section.</p></td></tr><tr><td style='padding: 15px;'><p>2. Relational Operators</p><p style='margin: 0'>This video explains relational operators.</p></td></tr><tr><td style='padding: 15px;'><p>3. Logical Operators</p><p style='margin: 0'>This video explains logical operators,</p></td></tr><tr><td style='padding: 15px;'><p>4. Conditional Statements</p><p style='margin: 0'>This video explains conditional statements.</p></td></tr><tr><td style='padding: 15px;'><p>5. Working with Loops</p><p style='margin: 0'>This video explains working with loops.</p></td></tr><tr><td style='padding: 15px;'><p>6. Working with Functions</p><p style='margin: 0'>This video explains working with functions in R.</p></td></tr><tr><td style='padding: 15px;'><p>7. Working with Packages</p><p style='margin: 0'>This video explains working with packages.</p></td></tr><tr><td style='padding: 15px;'><p>8. Working with Factors</p><p style='margin: 0'>This video explains working with factors in R.</p></td></tr><tr><td style='padding: 15px;'><p>9. Dates and Times</p><p style='margin: 0'>This video explains dates and times in R.</p></td></tr><tr><td style='padding: 15px;'><p>10. Functional Programming</p><p style='margin: 0'>This video explains functional programming.</p></td></tr><tr><td style='padding: 15px;'><p>11. Data Import/Export</p><p style='margin: 0'>This video explains how to import and export data in R.</p></td></tr><tr><td style='padding: 15px;'><p>12. Working with Databases</p><p style='margin: 0'>This video explains working with databases.</p></td></tr></tbody></table><br><h4>5. Data Manipulation in R</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Data Manipulation Section Introduction</p><p style='margin: 0'>This video introduces you to data manipulation.</p></td></tr><tr><td style='padding: 15px;'><p>2. Tidy Data</p><p style='margin: 0'>This video explains tidy data.</p></td></tr><tr><td style='padding: 15px;'><p>3. The Pipe Operator</p><p style='margin: 0'>This video explains pipe operator.</p></td></tr><tr><td style='padding: 15px;'><p>4. {dplyr}: The Filter Verb</p><p style='margin: 0'>This video explains the filter verb.</p></td></tr><tr><td style='padding: 15px;'><p>5. {dplyr}: The Select Verb</p><p style='margin: 0'>This video explains the select verb</p></td></tr><tr><td style='padding: 15px;'><p>6. {dplyr}: The Mutate Verb</p><p style='margin: 0'>This video explains the mutate verb.</p></td></tr><tr><td style='padding: 15px;'><p>7. {dplyr}: The Arrange Verb</p><p style='margin: 0'>This video explains the purpose of arrange verb.</p></td></tr><tr><td style='padding: 15px;'><p>8. {dplyr}: The Summarize Verb</p><p style='margin: 0'>This video explains the summarize verb.</p></td></tr><tr><td style='padding: 15px;'><p>9. Data Pivoting: {tidyr}</p><p style='margin: 0'>This video explains data pivoting.</p></td></tr><tr><td style='padding: 15px;'><p>10. String Manipulation: {stringr}</p><p style='margin: 0'>This video explains string manipulation.</p></td></tr><tr><td style='padding: 15px;'><p>11. Web Scraping: {rvest}</p><p style='margin: 0'>This video explains web scraping.</p></td></tr><tr><td style='padding: 15px;'><p>12. JSON Parsing: {jsonlite}</p><p style='margin: 0'>This video explains JSON parsing.</p></td></tr></tbody></table><br><h4>6. Data Visualization in R</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Data Visualization in R Section Introduction</p><p style='margin: 0'>This video explains data visualization in R.</p></td></tr><tr><td style='padding: 15px;'><p>2. Getting Started with Data Visualization in R</p><p style='margin: 0'>This video explains getting started with data visualization in R.</p></td></tr><tr><td style='padding: 15px;'><p>3. Aesthetics Mappings</p><p style='margin: 0'>This vide explains aesthetics mappings.</p></td></tr><tr><td style='padding: 15px;'><p>4. Single Variable Plots</p><p style='margin: 0'>This video focuses on single variable plots.</p></td></tr><tr><td style='padding: 15px;'><p>5. Two Variable Plots</p><p style='margin: 0'>This video explains two variable plots.</p></td></tr><tr><td style='padding: 15px;'><p>6. Facets, Layering, and Coordinate Systems</p><p style='margin: 0'>This video explains facets, layering, and coordinate systems.</p></td></tr><tr><td style='padding: 15px;'><p>7. Styling and Saving</p><p style='margin: 0'>This video explains styling and saving.</p></td></tr></tbody></table><br><h4>7. Creating Reports with R Markdown</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Introduction to R Markdown</p><p style='margin: 0'>This video is an introduction to R.</p></td></tr></tbody></table><br><h4>8. Building Webapps with R Shiny</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Introduction to R Shiny</p><p style='margin: 0'>This video is an introduction to R Shiny</p></td></tr><tr><td style='padding: 15px;'><p>2. Creating a Basic R Shiny App</p><p style='margin: 0'>This video helps you to create a basic R shiny app.</p></td></tr><tr><td style='padding: 15px;'><p>3. Other Examples with R Shiny</p><p style='margin: 0'>This video gives various examples with R shiny.</p></td></tr></tbody></table><br><h4>9. Introduction to Machine Learning</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Introduction to Machine Learning Part One</p><p style='margin: 0'>This video is an introduction to machine learning.</p></td></tr><tr><td style='padding: 15px;'><p>2. Introduction to Machine Learning Part Two</p><p style='margin: 0'>This video explains the different approaches in machine learning.</p></td></tr></tbody></table><br><h4>10. Data Preprocessing</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Data Preprocessing Introduction</p><p style='margin: 0'>This video introduces you to data preprocessing.</p></td></tr><tr><td style='padding: 15px;'><p>2. Data Preprocessing</p><p style='margin: 0'>This video explains some of the practical ways of data preprocessing.</p></td></tr></tbody></table><br><h4>11. Linear Regression: A Simple Model</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Linear Regression: A Simple Model Introduction</p><p style='margin: 0'>This video explains a simple linear regression model.</p></td></tr><tr><td style='padding: 15px;'><p>2. A Simple Model</p><p style='margin: 0'>This video demonstrates a practical application of machine learning.</p></td></tr></tbody></table><br><h4>12. Exploratory Data Analysis</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Exploratory Data Analysis Introduction</p><p style='margin: 0'>This video gives an introduction to exploratory data analysis.</p></td></tr><tr><td style='padding: 15px;'><p>2. Hands-on Exploratory Data Analysis</p><p style='margin: 0'>This video explains hands-on exploratory data analysis.</p></td></tr></tbody></table><br><h4>13. Linear Regression - a Real Model</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Linear Regression - Real Model Section Introduction</p><p style='margin: 0'>This video explains linear regression - a real model.</p></td></tr><tr><td style='padding: 15px;'><p>2. Linear Regression in R - Real Model</p><p style='margin: 0'>This video explains linear regression in R.</p></td></tr></tbody></table><br><h4>14. Logistic Regression</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Introduction to Logistic Regression</p><p style='margin: 0'>This video introduces you to logistic regression.</p></td></tr><tr><td style='padding: 15px;'><p>2. Logistic Regression in R</p><p style='margin: 0'>This video explains logistic regression in R.</p></td></tr></tbody></table><br><h4>15. Starting a Career in Data Science</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Starting a Data Science Career Section Overview</p><p style='margin: 0'>This video explains section overview of data science and career.</p></td></tr><tr><td style='padding: 15px;'><p>2. Creating a Data Science Resume</p><p style='margin: 0'>This video explains creating a data science resume.</p></td></tr><tr><td style='padding: 15px;'><p>3. Getting Started with Freelancing</p><p style='margin: 0'>This vide explains how to get started with freelancing.</p></td></tr><tr><td style='padding: 15px;'><p>4. Top Freelance Websites</p><p style='margin: 0'>This video focuses on top freelancing websites.</p></td></tr><tr><td style='padding: 15px;'><p>5. Personal Branding</p><p style='margin: 0'>This video explains personal branding.</p></td></tr><tr><td style='padding: 15px;'><p>6. Networking Do's and Don'ts</p><p style='margin: 0'>This video explains networking do's and don'ts.</p></td></tr><tr><td style='padding: 15px;'><p>7. Setting Up a Website</p><p style='margin: 0'>This video explains how to set up a website.</p></td></tr></tbody></table>

In this practical, hands-on course, you'll learn how to use R for effective data analysis and visualization and how to make use of that data in a practical manner. You will learn how to install and configure software necessary for a statistical programming environment and describe generic programming language concepts as they are implemented in a high-level statistical language.

Data Science and Machine Learning with R from A-Z Course [Updated for 2021]

Janets

Trainers Course

Data Science and Machine Learning using Python : A Bootcamp

Get involved in a learning adventure, mastering R from foundational basics to advanced techniques. This course is a gateway to the realm of data science. Explore statistical machine learning models and intricacies of deep learning and create interactive Shiny apps. Unleash the power of R and elevate your proficiency in data-driven decision-making.

R Ultimate 2023 - R for Data Science and Machine Learning

<section>
						<div>
				<div>
				<div>
			<div>
					<div>
				<div>
				<div>
					<div>
			<div></div>
		</div>
				</div>
				</div>
				<div>
				<div>
			
				</div>
				<div>
				<div>
					<div><p>Python has steadily ascended the ranks in the tech world, becoming the go-to language for Data Science and Machine Learning pursuits. Its versatility and ease of use make it an optimal choice for those aspiring to delve into the intricate realms of data analysis and algorithm development. By integrating Python into the curriculum, this course ensures that learners are not only familiar with the language but also proficient in its application to Data Science and Machine Learning tasks.</p><p>Data Science, on the other hand, stands as the backbone of today's analytical advancements. With the ever-growing quantum of data, there's a dire need for professionals who can sift through this data deluge and extract meaningful insights. This course simplifies complex topics, making it easier for learners to grasp the intricate mechanics of data manipulation, processing, and analysis. By emphasizing Python's role in Data Science, the course underscores its significance in modern-day data operations.</p><p>Lastly, Machine Learning represents the pinnacle of automated data analysis. With the power of Python and the methodologies of Data Science, Machine Learning enables systems to learn from data and make decisions. This course elucidates these concepts, teaching learners to design, implement, and test Machine Learning algorithms. The synergy of Python, Data Science, and Machine Learning in this curriculum ensures that, by the end, learners are well-equipped to tackle any data challenge that comes their way.</p></div>
				</div>
				</div>
						</div>
			</div>
		</div>
						</div>
			</div>
		</div></section>
				<section>
						<div>
				<div>
				<div>
			<div>
					<div>
				<div>
				<div>
			<h2><b> Learning outcome</b></h2>		</div>
				</div>
				<div>
				<div>
					<ul>
							<li>
											<span>
													</span>
										<span>Acquire in-depth knowledge of Data Science techniques using Python.</span>
									</li>
								<li>
											<span>
													</span>
										<span>Understand and implement Machine Learning algorithms.</span>
									</li>
								<li>
											<span>
													</span>
										<span>Analyze and visualize data with Python libraries like Pandas and Matplotlib.</span>
									</li>
								<li>
											<span>
													</span>
										<span>Evaluate and compare Machine Learning algorithms for optimum results.</span>
									</li>
								<li>
											<span>
													</span>
										<span>Develop real-time prediction models using trained datasets.</span>
									</li>
						</ul>
				</div>
				</div>
						</div>
			</div>
		</div>
						</div>
			</div>
		</section>
				<section>
						<div>
				<div>
				<div>
			<div>
					<div>
				<div>
				<div>
					</div>
				</div>
				<div>
				<div>
					
			</div>
				</div>
						</div>
			</div>
		</div>
						</div>
			</div>
		</section>
				<section>
						<div>
				<div>
				<div>
			<div>
					<div>
				<div>
				<div>
			<h2> <b>Why should I take this course?</b></h2>		</div>
				</div>
				<div>
				<div>
					<ul>
							<li>
											<span>
													</span>
										<span>Stay ahead in the rapidly growing field of Data Science and Machine Learning.</span>
									</li>
								<li>
											<span>
													</span>
										<span>Enhance career opportunities in the tech and data sectors.</span>
									</li>
								<li>
											<span>
													</span>
										<span>Learn to use Python, a leading programming language in Data Science.</span>
									</li>
								<li>
											<span>
													</span>
										<span>Address real-world business challenges using data analysis.</span>
									</li>
								<li>
											<span>
													</span>
										<span>Achieve proficiency in handling and visualizing large datasets.</span>
									</li>
						</ul>
				</div>
				</div>
						</div>
			</div>
		</div>
						</div>
			</div>
		</section>
				<section>
						<div>
				<div>
				<div>
			<div>
					<div>
				<div>
				<div>
			<h2> <b>Career Path</b></h2>		</div>
				</div>
				<div>
				<div>
					<ul>
							<li>
											<span>
													</span>
										<span>Data Scientist</span>
									</li>
								<li>
											<span>
													</span>
										<span>Machine Learning Engineer</span>
									</li>
								<li>
											<span>
													</span>
										<span>Python Data Analyst</span>
									</li>
								<li>
											<span>
													</span>
										<span>Predictive Modeler</span>
									</li>
								<li>
											<span>
													</span>
										<span>Data Visualization Expert</span>
									</li>
						</ul>
				</div>
				</div>
						</div>
			</div>
		</div>
						</div>
			</div>
		</section>
				<section>
						<div>
				<div>
				<div>
			<div>
					<div>
				<div>
				<div>
			<h2> <b>Requirements</b></h2>		</div>
				</div>
				<div>
				<div>
					<ul>
							<li>
											<span>
													</span>
										<span>Basic understanding of programming concepts.</span>
									</li>
								<li>
											<span>
													</span>
										<span>Eagerness to learn Data Science and Machine Learning.</span>
									</li>
								<li>
											<span>
													</span>
										<span>A computer with internet access.</span>
									</li>
						</ul>
				</div>
				</div>
						</div>
			</div>
		</div>
						</div>
			</div>
		</section>

Skill Up

Master Data Science and Machine Learning with Python to transform data-driven decisions in businesses.

Data Science & Machine Learning with Python

<strong>In the fast-paced world of data science and machine learning, you have to stay up-to-date and keep ahead of the competition. For this, you have to constantly be on the lookout for the latest trends in tools and techniques for data science and machine learning. You don't want to miss out on the latest trend and the tool of the future! Right now, that tool is the Julia programming language. It's the hot new language that all ML and data science experts are very excited about. Learning Julia will open up several doors for you in your career!</strong>
        <p>The objective of this course is to give you a strong foundation needed to excel in Julia and learn the core of the language as well as the applied side in the shortest amount of time possible.

We won't waste time with the theory of why Julia is fast. We will jump right into the details and start coding. You will quickly realize how easy it is to learn this state-of-the-art and promising language. You will see how you can start using Julia to excel in your current job without moving the whole stack to Julia immediately.

After explaining the basic concepts, we jump to case studies in data science and then machine learning. We apply both traditional machine learning models and then get to deep learning. You will see how Julia can help you create deep learning models from scratch in just a few lines of code and then move on to the state-of-the-art models without spending too much time.

This way, you get to learn the most important concepts in this subject in the shortest amount of time possible without having to deal with the details of the less relevant topics. Once you have developed an intuition of the important stuff, you can then learn the latest and greatest models even on your own!

By the end of the course, you will have a strong understanding of Julia programming language fundamentals.
The code files are available here: https://github.com/PacktPublishing/Julia-Programming-Language---From-Zero-to-Expert-</p>
        <h2>What You Will Learn</h2><p>Learn coding in Julia programming language<br>Use DataFrames (equivalent to Pandas) in Julia<br>Create ML models from scratch in a way that helps you make modifications easily<br>Learn data wrangling with Julia<br>Use Julia to perform data manipulation, Apache Arrow, grouping, and analysis<br>Classify using decision trees and random forests</p>
        <h2>Audience</h2><p>This course is for all levels of data science and machine learning practitioners aiming to enhance their abilities and skill level in DS and ML. Developers who want to know how to harness the power of big data can also go for this course.<br><br>A basic understanding of programming is a must. Understanding Python, basic data science (reading CSVs and so on), and basic concepts of deep learning (such as classification) is not necessary but would be helpful.</p>
        <h2>Approach</h2><p>This course follows a code-oriented and case-study-based approach. In this course, you will learn by practice as every concept explanation is followed by practical implementation.</p>
        <h2>Key Features</h2><p>Learn the syntax of Julia and its differences from Python * Learn machine learning models, both traditional and deep * Explore data science case studies, including analysis and clustering</p>
        <h2>Github Repo</h2><p>https://github.com/PacktPublishing/Julia-Programming-Language---From-Zero-to-Expert-</p>
        <h2>About the Author</h2><h3>Dr. Mohammad Nauman</h3><p>Dr. Mohammad Nauman has a PhD in computer science and a PostDoc from the Max Planck Institute for software systems. He has been programming since early 2000 and has worked with many different languages, tools, and platforms. He holds extensive research experience with many state-of-the-art models. His research in Android security has led to some major shifts in the Android permission model.
He loves teaching and the most important reason he teaches online is to make sure that maximum people can learn through his content. Hope you have fun learning with him!</p>
        <h2>Course Outline</h2><h4>1. Intro and Setting up</h4><p></p><br><h4>2. Core Language Basics</h4><p></p><br><h4>3. Arrays and Matrices: Native Language Support</h4><p></p><br><h4>4. Functions and Fun Stuff</h4><p></p><br><h4>5. Getting Started with Data Science</h4><p></p><br><h4>6. Case Studies in Data Science</h4><p></p><br><h4>7. Deep Learning - Flux in Julia</h4><p></p><br><h4>8. Parting Words</h4><p></p>

Programming

In the fast-paced world of data science and machine learning, you have to stay up-to-date and keep ahead of the competition. For this, you have to constantly be on the lookout for the latest trends in tools and techniques for data science and machine learning. You don't want to miss out on the latest trend and the tool of the future! Right now, that tool is the Julia programming language. It's the hot new language that all ML and data science experts are very excited about. Learning Julia will open up several doors for you in your career!

266 Courses

Data Analytics with Tableau Diploma

By Academy for Health and Fitness

DP-090T00: Implementing a Machine Learning Solution with Microsoft Azure Databricks

By Nexus Human

Data Analyst (Data Analytics) Diploma - CPD Certified

By Apex Learning

Assessment Based Training - Python Programming & Analytics for the Oil & Gas Sector - Maximising Value from Data Assets

By EnergyEdge - Training for a Sustainable Energy Future

Assessment Based Training – Python Programming & Analytics for the Oil & Gas Sector – Maximising Value from Data Assets

By EnergyEdge - Training for a Sustainable Energy Future

Machine Learning and Data Science with Python: A Complete Beginners Guide

By Packt

Data Engineering - CPD Certified

By Academy for Health and Fitness

Python, Data Science, Machine Learning, SQL, Cloud computing & Cyber Security

By Compliance Central

Python Programming at QLS Level 7 Course

By One Education

Python Programming at QLS Level 7 Course

By One Education

Search By Location