685 PIP courses delivered Online

Overview This comprehensive course on Baking & Cake Decorating Online Diploma Course will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Baking & Cake Decorating Online Diploma Course comes with accredited certification, which will enhance your CV and make you worthy in the job market. So enrol in this course today to fast track your career ladder. How will I get my certificate? You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate. Who is This course for? There is no experience or previous qualifications required for enrolment on this Baking & Cake Decorating Online Diploma Course. It is available to all students, of all academic backgrounds Requirements Our Baking & Cake Decorating Online Diploma Course is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G. There is no time limit for completing this course, it can be studied in your own time at your own pace. Career Path Having these various qualifications will increase the value in your CV and open you up to multiple sectors such as Business & Management, Admin, Accountancy & Finance, Secretarial & PA, Teaching & Mentoring etc.   Course Curriculum 17 sections • 17 lectures • 06:02:00 total length •Basic Concepts of Baking: 00:16:00 •Basic Ingredients of Baking: 00:28:00 •Glossary and Equipment Used in Baking: 00:36:00 •Types of Cakes: 00:14:00 •Baking the Cake: 00:20:00 •Baking Principles: 00:25:00 •Cake Decorating Recipes: 00:26:00 •Cake Decorating Ideas: 00:21:00 •Frosting and Icing: 00:24:00 •Working with Different Pastes: 00:20:00 •Working with Glazes: 00:28:00 •How to Stack a Cake: 00:21:00 •Piping and Writing: 00:24:00 •Health, Safety and Food Hygiene: 00:20:00 •Troubleshooting: 00:20:00 •Cake Decorating Business: 00:19:00 •Assignment - Baking & Cake Decorating Online Diploma Course: 00:00:00

Overview This comprehensive course on Creating Highly Profitable Sales Funnels will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Creating Highly Profitable Sales Funnels comes with accredited certification from CPD, which will enhance your CV and make you worthy in the job market. So enrol in this course today to fast-track your career ladder. How will I get my certificate? You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate. Who is This course for? There is no experience or previous qualifications required for enrolment on this Creating Highly Profitable Sales Funnels. It is available to all students, of all academic backgrounds. Requirements Our Creating Highly Profitable Sales Funnels is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G. There is no time limit for completing this course, it can be studied in your own time at your own pace. Career Path Learning this new skill will help you to advance in your career. It will diversify your job options and help you develop new techniques to keep up with the fast-changing world. This skillset will help you to- Open doors of opportunities Increase your adaptability Keep you relevant Boost confidence And much more! Course Curriculum 6 sections • 17 lectures • 01:26:00 total length •What is a Sales Funnel?: 00:02:00 •Why ALL Businesses Need Sales Funnels: 00:05:00 •3 Phases of a Highly Converting Sales Funnel: 00:03:00 •The 4 Sales Funnel Stages: 00:04:00 •Macro and Micro Conversions: 00:03:00 •What is Market Sophistication?: 00:01:00 •The 5 Stages of Market Sophistication: 00:06:00 •Sales Pipeline vs Sales Funnel: 00:02:00 •The Perfect Simple 3 Step Local Business Sales Funnel: 00:05:00 •The Perfect Simple 4 Step Digital Products Sales Funnel: 00:05:00 •How to Create The Perfect Lead Magnet: 00:04:00 •Landing Page Design Elements: 00:07:00 •Landing Page Design Walkthrough: 00:14:00 •Different Types of Sales Funnels: 00:11:00 •Key Sales Funnel Metrics: 00:04:00 •How Write Copy That Turns Traffic In Customers: 00:10:00 •Assignment - Creating Highly Profitable Sales Funnels: 00:00:00

Overview This comprehensive course on WebGL 2D/3D Programming and Graphics Rendering will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This WebGL 2D/3D Programming and Graphics Rendering comes with accredited certification, which will enhance your CV and make you worthy in the job market.So enrol in this course today to fast track your career ladder. How will I get my certificate? After successfully completing the course you will be able to order your certificate, these are included in the price. Who is This course for? There is no experience or previous qualifications required for enrolment on this WebGL 2D/3D Programming and Graphics Rendering. It is available to all students, of all academic backgrounds. Requirements Our WebGL 2D/3D Programming and Graphics Rendering is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G.There is no time limit for completing this course, it can be studied in your own time at your own pace. Career Path Having these various qualifications will increase the value in your CV and open you up to multiple sectors such as Business & Management, Admin, Accountancy & Finance, Secretarial & PA, Teaching & Mentoring etc. Course Curriculum 7 sections • 28 lectures • 04:05:00 total length •WebGL vs OpenGL vs OpenGL ES: 00:05:00 •Setup Server (Mac, Windows and Linux): 00:05:00 •Setup WebGL Project: 00:08:00 •WebGL Rendering Pipeline: 00:04:00 •Drawing A Point: 00:22:00 •Normalised Coordinates vs Device Coordinates: 00:10:00 •Drawing A Simple Triangle: 00:06:00 •Drawing A Line Using gl.LINES: 00:03:00 •Drawing A Line Using gl.LINE_STRIP & gl.LINE_LOOP: 00:03:00 •Drawing A Triangle With Lines Using gl.TRIANGLE_STRIP & gl.TRIANGLE_FAN: 00:03:00 •Drawing A Quad: 00:07:00 •Drawing A 3D Cube: 00:24:00 •Setup Three.js: 00:06:00 •Loading & Drawing A Model Using Three.js: 00:16:00 •Applying Color To Shapes: 00:09:00 •One Color Per Triangle: 00:15:00 •One Color Per Vertex Using Interpolation: 00:02:00 •Applying A Texture To Shapes: 00:23:00 •Texture Coordinates: 00:08:00 •Moving Objects Using Translation: 00:06:00 •Left Handed vs Right Handed Coordinate System: 00:06:00 •Sizing Objects Using Scaling: 00:06:00 •Combining Transformations: 00:07:00 •Mouse Input: 00:11:00 •Keyboard Input: 00:09:00 •Fixing Rotation and Adding Individual Rotation: 00:08:00 •Ambient Lighting: 00:13:00 •Resource: 00:00:00

Overview Don't listen to 'Fake News' and Conspiracy Theories. Learn the facts about Climate Change and how you can make a difference. This innovative course will enlighten and educate you with scientifically proven facts about the world's changing environment and the challenges ahead. The Solving Climate Change Problems with Renewable Energy course has been written with the assistance of industry professionals and is designed to give you the complete and verified details about Climate Change. You will be taught about current weather patterns and ongoing pollution concerns. The content also covers sustainable energy sources and the achievable goals that everyone should attempt. Know the truth and become 'greener' today. How will I get my certificate? At the end of the course there will be a written assignment test which you can take either during or after the course. After successfully completing the test you will be able to order your certificate, these are included in the price. Who is this course for? There is no experience or previous qualifications required for enrolment on this Solving Climate Change Problems with Renewable Energy. It is available to all students, of all academic backgrounds. Requirements Our Solving Climate Change Problems with Renewable Energy is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible on tablets and smartphones so you can access your course on wifi, 3G or 4G. There is no time limit for completing this course, it can be studied in your own time at your own pace. Career path Having these various qualifications will increase the value in your CV and open you up to multiple sectors such as Business & Management , Admin, Accountancy & Finance, Secretarial & PA, Teaching & Mentoring etc. Course Curriculum 3 sections • 32 lectures • 19:25:00 total length •Introduction: 00:30:00 •What is Renewable Energy?: 00:30:00 •Types of Renewable Energy: 00:15:00 •Solar Power: 00:30:00 •Wind Power: 01:00:00 •Hydropower: 01:00:00 •Biofuel: 00:30:00 •The Possibilities of Renewable Energy: 01:00:00 •Government Incentives: 01:00:00 •Renewable Energy Is Key to Fighting Climate Change: 01:00:00 •Energy Audits: 01:00:00 •LEED: 01:00:00 •BREEAM: 01:00:00 •EPC: 01:00:00 •How to Choose Your Renewable Energy Sources: 01:00:00 •The Advantages and Disadvantages of Renewable Energy: 01:00:00 •Solar Geometry: 01:00:00 •Solar Chimney: 00:30:00 •Solar Wall: 00:30:00 •PV/Thermal: 00:10:00 •Solar Water Heaters: 00:30:00 •Solar Water Heaters: 00:30:00 •Solar Photovoltaic Technology Basics: 00:30:00 •Other Energy Saving Technologies: 00:15:00 •Underground Thermal Energy Storage (UTES): 00:15:00 •Trigeneration / CCHP: 00:15:00 •Rainwater Harvesting: 00:15:00 •Fuel Cell: 00:45:00 •Earth Duct: 00:15:00 •Light Pipe: 00:15:00 •Conclusion: 00:15:00 •Assignment - Solving Climate Change Problems with Renewable Energy: 00:00:00

Overview This comprehensive course on Machine Learning for Predictive Maps in Python and Leaflet will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Machine Learning for Predictive Maps in Python and Leaflet comes with accredited certification from CPD, which will enhance your CV and make you worthy in the job market. So enrol in this course today to fast track your career ladder. How will I get my certificate? You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate. Who is This course for? There is no experience or previous qualifications required for enrolment on this Machine Learning for Predictive Maps in Python and Leaflet. It is available to all students, of all academic backgrounds. Requirements Our Machine Learning for Predictive Maps in Python and Leaflet is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G. There is no time limit for completing this course, it can be studied in your own time at your own pace. Career Path Learning this new skill will help you to advance in your career. It will diversify your job options and help you develop new techniques to keep up with the fast-changing world. This skillset will help you to- Open doors of opportunities Increase your adaptability Keep you relevant Boost confidence And much more! Course Curriculum 9 sections • 33 lectures • 05:59:00 total length •Introduction: 00:10:00 •Python Installation: 00:04:00 •Creating a Python Virtual Environment: 00:07:00 •Installing Django: 00:09:00 •Installing Visual Studio Code IDE: 00:06:00 •Installing PostgreSQL Database Server Part 1: 00:03:00 •Installing PostgreSQL Database Server Part 2: 00:09:00 •Adding the settings.py Code: 00:07:00 •Creating a Django Model: 00:10:00 •Adding the admin.py Code: 00:21:00 •Creating Template Files: 00:10:00 •Creating Django Views: 00:10:00 •Creating URL Patterns for the REST API: 00:09:00 •Adding the index.html code: 00:04:00 •Adding the layout.html code: 00:19:00 •Creating our First Map: 00:10:00 •Adding Markers: 00:16:00 •Installing Jupyter Notebook: 00:07:00 •Data Pre-processing: 00:31:00 •Model Selection: 00:20:00 •Model Evaluation and Building a Prediction Dataset: 00:11:00 •Creating a Django Model: 00:04:00 •Embedding the Machine Learning Pipeline in the Application: 00:42:00 •Creating a URL Endpoint for our Prediction Dataset: 00:06:00 •Creating Multiple Basemaps: 00:09:00 •Creating the Marker Layer Group: 00:10:00 •Creating the Point Layer Group: 00:12:00 •Creating the Predicted Point Layer Group: 00:07:00 •Creating the Predicted High Risk Point Layer Group: 00:12:00 •Creating the Legend: 00:09:00 •Creating the Prediction Score Legend: 00:15:00 •Resource: 00:00:00 •Assignment - Machine Learning for Predictive Maps in Python and Leaflet: 00:00:00

The 'Logistics of Crude Oil and Petroleum Products' course provides a comprehensive understanding of the various methods of transporting crude oil and petroleum products. From marine transport to pipeline operations and storage, learners will gain insights into the crucial logistics involved in the petroleum industry. Learning Outcomes: Identify the different methods of transporting crude oil and petroleum products. Understand the logistics and operations involved in marine transport and pipeline systems. Compare the costs associated with different transportation methods. Gain knowledge of storage and delivery processes to refineries. Learn about the dispatch of petroleum products and the controls implemented during the process. Why buy this Logistics of Crude Oil and Petroleum Products? Unlimited access to the course for forever Digital Certificate, Transcript, student ID all included in the price Absolutely no hidden fees Directly receive CPD accredited qualifications after course completion Receive one to one assistance on every weekday from professionals Immediately receive the PDF certificate after passing Receive the original copies of your certificate and transcript on the next working day Easily learn the skills and knowledge from the comfort of your home Certification After studying the course materials of the Logistics of Crude Oil and Petroleum Products there will be a written assignment test which you can take either during or at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £5.99. Original Hard Copy certificates need to be ordered at an additional cost of £9.60. Who is this course for? This Logistics of Crude Oil and Petroleum Products course is ideal for Students Recent graduates Job Seekers Anyone interested in this topic People already working in the relevant fields and want to polish their knowledge and skill. Prerequisites This Logistics of Crude Oil and Petroleum Products does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Logistics of Crude Oil and Petroleum Products was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Career path As this course comes with multiple courses included as bonus, you will be able to pursue multiple occupations. This Logistics of Crude Oil and Petroleum Products is a great way for you to gain multiple skills from the comfort of your home. Course Curriculum Unit 01: About The Course Learning objectives 00:04:00 Unit 02: The Different Methods of Transport Introduction to the different methods of transport 00:05:00 Unit 03: Marine Transport The different types of tankers 00:05:00 The different types of charters 00:02:00 The cost of marine transport 00:04:00 Prices and costs of marine transport 00:05:00 Prices and costs of marine transport 00:05:00 Regulations : National flag requirement 00:01:00 Flags of convenience 00:01:00 Operating aspects 00:04:00 Controls on loading 00:07:00 Administrative formalities 00:01:00 The reception of tankers 00:07:00 Unit 04: Transport by Pipeline The constraints 00:05:00 The cost of transport by pipeline 00:03:00 Unit 05: Comparing Transport Costs Comparing transport costs 00:06:00 Unit 06: Storage and Delivery to the Refinery Storage and delivery to the refinery 00:03:00 Unit 07: Dispatch of Petroleum Products Introduction 00:03:00 Dispatch by pipeline 00:07:00 Dispatch by water 00:07:00 Dispatch by rail 00:06:00 Dispatch by road 00:05:00 Unit 08: Controls at Dispatch Quality 00:02:00 Quantities 00:02:00 Administrative accounting methods 00:01:00 Customs formalities 00:02:00 Assignment Assignment - Logistics of Crude Oil and Petroleum Products 00:00:00

Imagine immersing yourself in the thrilling world of game development, where your creative ideas come to life on the screen. Our Flappy Bird Clone: SFML C++ Game Course offers you a golden ticket to the vibrant heart of the entertainment industry, equipping you with the tools to shape your interactive stories. By mastering SFML and C++, you'll unlock the door to a realm of endless possibilities, where you can recreate the beloved Flappy Bird game or even craft your very own gaming masterpiece. Picture yourself skillfully navigating through each stage of game development, from the initial project setup to the intricate intricacies of game engines and flow control. This is not just about gaining technical skills; it's about cultivating a keen problem-solving mindset that will guide you through any challenges you encounter in your development journey. With each lesson, you'll feel a growing sense of accomplishment and confidence, propelling you closer to your ultimate gaming dream. Now, envision the pride and joy you'll experience as you watch your game come to life, a testament to your hard work and dedication. This Flappy Bird Clone: SFML C++ Game Course isn't just a learning experience; it's a personal journey that taps into your passion and potential, ultimately leading you to your desired destination, be it personal satisfaction, professional growth, or even launching your own game. Take the leap and enrol now, and let's turn those dreams into a tangible, interactive reality that others can experience and enjoy. Learning Outcomes Master the basics of game development in SFML C++. Develop skills in setting up a game project efficiently. Gain proficiency in implementing game engines and mechanics. Learn to create various states for game flow control. Understand and apply game logic for better player experience. Learn to implement game-over scenarios and player retries. Enhance skills in adding extra features to games. Gain knowledge on efficiently managing game resources. Who is this course for? Aspiring game developers looking to enhance their skills. Individuals with an interest in game design and development. Professionals seeking to expand their knowledge in C++ and SFML. Students studying computer science or related fields. Anyone with a passion for games and a curiosity to understand their mechanics. Career Path Game Developer: £25,000 - £50,000 Software Engineer: £30,000 - £70,000 C++ Developer: £30,000 - £60,000 Game Designer: £25,000 - £40,000 Application Developer: £25,000 - £50,000 Certification Once you have completed the course materials for the Flappy Bird Clone: SFML C++ Game Course, you will have the opportunity to take a written assignment test. This can be done either during or at the end of the course. Successful completion of the test will allow you to claim your PDF certificate for a nominal fee of £5.99. If you prefer, original hard copy certificates can be ordered for an additional cost of £9.60. Prerequisites There are no specific qualifications or experience required to enrol in the Flappy Bird Clone: SFML C++ Game Course. Crafted by industry professionals, the course is compatible with PCs, Macs, tablets, and smartphones. As long as you have a stable internet connection, you will have the flexibility to access the course material from anywhere at any time. Course Curriculum Section 01: Introduction Introduction 00:02:00 Section 02: Project Creation & Setup Setup Project - Windows (Visual Studio) 00:14:00 Setup Project - Mac OS X (Xcode) 00:11:00 Section 03: Game Engine Setup State Machine 00:18:00 Asset Manager 00:08:00 Input Manager 00:08:00 Game Loop 00:14:00 Section 04: State Creation Splash State 00:17:00 Main Menu State 00:16:00 Game State 00:07:00 Game Over State 00:04:00 Section 05: Game Logic Pipe Class Setup 00:08:00 Spawn Moving Pipes 00:11:00 Automatically Spawning Pipes and Deleting Them 00:08:00 Create Moving Ground 00:14:00 Randomise Pipe Y Position 00:06:00 Bird Class Setup 00:10:00 Animating the Bird 00:08:00 Fly Bird Fly 00:11:00 Rotate Bird 00:06:00 Collision with the Ground & Game State System 00:15:00 Collision with the Pipes 00:09:00 Flash Screen White upon Death 00:12:00 Scoring System 00:15:00 Displaying the Score 00:18:00 Section 06: Game Over Setup 00:16:00 Display Score 00:08:00 Saving Score 00:06:00 Medals 00:08:00 Section 07: Extras Sound Effects 00:08:00 Hide Console on Windows 00:01:00 Distributing Your Game on Windows 00:03:00 Where to Go Next? 00:07:00 Section 08: Resource Resource - Flappy Bird Clone: SFML C++ Game Course 00:00:00 Assignment Assignment - Flappy Bird Clone: SFML C++ Game Course 00:00:00

Overview This comprehensive course on Learn Linux in 5 Days will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Learn Linux in 5 Days comes with accredited certification from CPD, which will enhance your CV and make you worthy in the job market. So enrol in this course today to fast track your career ladder. How will I get my certificate? You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate. Who is This course for? There is no experience or previous qualifications required for enrolment on this Learn Linux in 5 Days. It is available to all students, of all academic backgrounds. Requirements Our Learn Linux in 5 Days is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G. There is no time limit for completing this course, it can be studied in your own time at your own pace. Career Path Learning this new skill will help you to advance in your career. It will diversify your job options and help you develop new techniques to keep up with the fast-changing world. This skillset will help you to- Open doors of opportunities Increase your adaptability Keep you relevant Boost confidence And much more! Course Curriculum 10 sections • 45 lectures • 05:58:00 total length •Course Overview: 00:03:00 •Background and Introduction: 00:07:00 •Linux Distributions: 00:05:00 •Installing VirtualBox on Windows: 00:03:00 •Installing VirtualBox on Mac: 00:03:00 •Installing Linux Using an Image for VirtualBox: 00:05:00 •VirtualBox Troubleshooting Tips: 00:02:00 •When to Install Linux from Scratch: 00:15:00 •Installing CentOS from Scratch / CentOS Manual Installation Process: 00:23:00 •Getting Connected: 00:11:00 •Connect Directly: 00:02:00 •The Linux Directory Structure: 00:10:00 •The Shell: 00:08:00 •Basic Linux Commands: 00:05:00 •Teach Yourself to Fish: 00:06:00 •Working with Directories: 00:09:00 •Listing Files and Understanding LS Output: 00:12:00 •File and Directory Permissions Explained - Part One: 00:11:00 •File and Directory Permissions Explained - Part Two: 00:09:00 •View Files and the Nano Editor: 00:05:00 •Editing Files in Vi: 00:10:00 •Editing Files with Emacs: 00:06:00 •Finding Files and Directories: 00:07:00 •Graphical Editors: 00:04:00 •Deleting, Copying, Moving, and Renaming Files: 00:11:00 •Wildcards - Part One: 00:05:00 •Wildcards - Part Two: 00:07:00 •Input, Output, and Redirection: 00:08:00 •Comparing Files: 00:04:00 •Searching in Files and Using Pipes: 00:10:00 •Transferring and Copying Files over the Network: 00:07:00 •Customizing the Shell Prompt: 00:05:00 •Shell Aliases: 00:04:00 •Environment Variables: 00:08:00 •Processes and Job Control: 00:12:00 •Scheduling Repeated Jobs with Cron: 00:06:00 •Switching Users and Running Commands as Others: 00:08:00 •Shell History and Tab Completion: 00:13:00 •Installing Software on RPM Based Linux Distros: RedHat, CentOS, AlmaLinux, Rocky: 00:21:00 •Installing Software on Debian Based Linux Distros: Debian, Ubuntu, Kali Linux: 00:12:00 •Conclusion - Congratulations and Thank You!: 00:01:00 •Connecting to a Linux Virtual Machine over the Network: 00:11:00 •Bonus - Installing NGINX, MySQL, PHP, and WordPress on Ubuntu: 00:09:00 •Resources: 00:15:00 •Assignment - Learn Linux in 5 Days: 00:00:00

Overview This comprehensive course on Data Science & Machine Learning with R will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Data Science & Machine Learning with R comes with accredited certification, which will enhance your CV and make you worthy in the job market. So enrol in this course today to fast track your career ladder. How will I get my certificate? You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate. Who is This course for? There is no experience or previous qualifications required for enrolment on this Data Science & Machine Learning with R. It is available to all students, of all academic backgrounds. Requirements Our Data Science & Machine Learning with R is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G. There is no time limit for completing this course, it can be studied in your own time at your own pace. Career Path Having these various qualifications will increase the value in your CV and open you up to multiple sectors such as Business & Management, Admin, Accountancy & Finance, Secretarial & PA, Teaching & Mentoring etc. Course Curriculum 10 sections • 69 lectures • 22:07:00 total length •Data Science and Machine Learning Introduction: 00:03:00 •What is Data Science: 00:10:00 •Machine Learning Overview: 00:05:00 •Who is This Course for: 00:03:00 •Data Science and Machine Learning Marketplace: 00:05:00 •Data Science and Machine Learning Job Opportunities: 00:03:00 •Getting Started: 00:11:00 •Basics: 00:06:00 •Files: 00:11:00 •RStudio: 00:07:00 •Tidyverse: 00:05:00 •Resources: 00:04:00 •Unit Introduction: 00:30:00 •Basic Type: 00:09:00 •Vector Part One: 00:20:00 •Vectors Part Two: 00:25:00 •Vectors - Missing Values: 00:16:00 •Vectors - Coercion: 00:14:00 •Vectors - Naming: 00:10:00 •Vectors - Misc: 00:06:00 •Creating Matrics: 00:31:00 •List: 00:32:00 •Introduction to Data Frames: 00:19:00 •Creating Data Frames: 00:20:00 •Data Frames: Helper Functions: 00:31:00 •Data Frames Tibbles: 00:39:00 •Intermediate Introduction: 00:47:00 •Relational Operations: 00:11:00 •Conditional Statements: 00:11:00 •Loops: 00:08:00 •Functions: 00:14:00 •Packages: 00:11:00 •Factors: 00:28:00 •Dates and Times: 00:30:00 •Functional Programming: 00:37:00 •Data Import or Export: 00:22:00 •Database: 00:27:00 •Data Manipulation in R Introduction: 00:36:00 •Tidy Data: 00:11:00 •The Pipe Operator: 00:15:00 •The Filter Verb: 00:22:00 •The Select Verb: 00:46:00 •The Mutate Verb: 00:32:00 •The Arrange Verb: 00:10:00 •The Summarize Verb: 00:23:00 •Data Pivoting: 00:43:00 •JSON Parsing: 00:11:00 •String Manipulation: 00:33:00 •Web Scraping: 00:59:00 •Data Visualization in R Section Intro: 00:17:00 •Getting Started: 00:16:00 •Aesthetics Mappings: 00:25:00 •Single Variable Plots: 00:37:00 •Two Variable Plots: 00:21:00 •Facets, Layering, and Coordinate Systems: 00:18:00 •Styling and Saving: 00:12:00 •Creating with R Markdown: 00:29:00 •Introduction to R Shiny: 00:26:00 •A Basic R Shiny App: 00:31:00 •Other Examples with R Shiny: 00:34:00 •Machine Learning Part 1: 00:22:00 •Machine Learning Part 2: 00:47:00 •Starting a Data Science Career Section Overview: 00:03:00 •Data Science Resume: 00:04:00 •Getting Started with Freelancing: 00:05:00 •Top Freelance Websites: 00:05:00 •Personal Branding: 00:05:00 •Importance of Website and Blo: 00:04:00 •Networking Do's and Don'ts: 00:04:00

The 'Complete Python Machine Learning & Data Science Fundamentals' course covers the foundational concepts of machine learning, data science, and Python programming. It includes hands-on exercises, data visualization, algorithm evaluation techniques, feature selection, and performance improvement using ensembles and parameter tuning. Learning Outcomes: Understand the fundamental concepts and types of machine learning, data science, and Python programming. Learn to prepare the system and environment for data analysis and machine learning tasks. Master the basics of Python, NumPy, Matplotlib, and Pandas for data manipulation and visualization. Gain insights into dataset summary statistics, data visualization techniques, and data preprocessing. Explore feature selection methods and evaluation metrics for classification and regression algorithms. Compare and select the best machine learning model using pipelines and ensembles. Learn to export, save, load machine learning models, and finalize the chosen models for real-time predictions. Why buy this Complete Python Machine Learning & Data Science Fundamentals? Unlimited access to the course for forever Digital Certificate, Transcript, student ID all included in the price Absolutely no hidden fees Directly receive CPD accredited qualifications after course completion Receive one to one assistance on every weekday from professionals Immediately receive the PDF certificate after passing Receive the original copies of your certificate and transcript on the next working day Easily learn the skills and knowledge from the comfort of your home Certification After studying the course materials of the Complete Python Machine Learning & Data Science Fundamentals there will be a written assignment test which you can take either during or at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £5.99. Original Hard Copy certificates need to be ordered at an additional cost of £9.60. Who is this course for? This Complete Python Machine Learning & Data Science Fundamentals course is ideal for Students Recent graduates Job Seekers Anyone interested in this topic People already working in the relevant fields and want to polish their knowledge and skill. Prerequisites This Complete Python Machine Learning & Data Science Fundamentals does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Complete Python Machine Learning & Data Science Fundamentals was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Career path As this course comes with multiple courses included as bonus, you will be able to pursue multiple occupations. This Complete Python Machine Learning & Data Science Fundamentals is a great way for you to gain multiple skills from the comfort of your home. Course Curriculum Course Overview & Table of Contents Course Overview & Table of Contents 00:09:00 Introduction to Machine Learning - Part 1 - Concepts , Definitions and Types Introduction to Machine Learning - Part 1 - Concepts , Definitions and Types 00:05:00 Introduction to Machine Learning - Part 2 - Classifications and Applications Introduction to Machine Learning - Part 2 - Classifications and Applications 00:06:00 System and Environment preparation - Part 1 System and Environment preparation - Part 1 00:08:00 System and Environment preparation - Part 2 System and Environment preparation - Part 2 00:06:00 Learn Basics of python - Assignment Learn Basics of python - Assignment 1 00:10:00 Learn Basics of python - Assignment Learn Basics of python - Assignment 2 00:09:00 Learn Basics of python - Functions Learn Basics of python - Functions 00:04:00 Learn Basics of python - Data Structures Learn Basics of python - Data Structures 00:12:00 Learn Basics of NumPy - NumPy Array Learn Basics of NumPy - NumPy Array 00:06:00 Learn Basics of NumPy - NumPy Data Learn Basics of NumPy - NumPy Data 00:08:00 Learn Basics of NumPy - NumPy Arithmetic Learn Basics of NumPy - NumPy Arithmetic 00:04:00 Learn Basics of Matplotlib Learn Basics of Matplotlib 00:07:00 Learn Basics of Pandas - Part 1 Learn Basics of Pandas - Part 1 00:06:00 Learn Basics of Pandas - Part 2 Learn Basics of Pandas - Part 2 00:07:00 Understanding the CSV data file Understanding the CSV data file 00:09:00 Load and Read CSV data file using Python Standard Library Understanding the CSV data file 00:09:00 Load and Read CSV data file using NumPy Load and Read CSV data file using Python Standard Library 00:09:00 Load and Read CSV data file using Pandas Load and Read CSV data file using Pandas 00:05:00 Dataset Summary - Peek, Dimensions and Data Types Dataset Summary - Peek, Dimensions and Data Types 00:09:00 Dataset Summary - Class Distribution and Data Summary Dataset Summary - Class Distribution and Data Summary 00:09:00 Dataset Summary - Explaining Correlation Dataset Summary - Explaining Correlation 00:11:00 Dataset Summary - Explaining Skewness - Gaussian and Normal Curve Dataset Summary - Explaining Skewness - Gaussian and Normal Curve 00:07:00 Dataset Visualization - Using Histograms Dataset Visualization - Using Histograms 00:07:00 Dataset Visualization - Using Density Plots Dataset Visualization - Using Density Plots 00:06:00 Dataset Visualization - Box and Whisker Plots Dataset Visualization - Box and Whisker Plots 00:05:00 Multivariate Dataset Visualization - Correlation Plots Multivariate Dataset Visualization - Correlation Plots 00:08:00 Multivariate Dataset Visualization - Scatter Plots Multivariate Dataset Visualization - Scatter Plots 00:05:00 Data Preparation (Pre-Processing) - Introduction Data Preparation (Pre-Processing) - Introduction 00:09:00 Data Preparation - Re-scaling Data - Part 1 Data Preparation - Re-scaling Data - Part 1 00:09:00 Data Preparation - Re-scaling Data - Part 2 Data Preparation - Re-scaling Data - Part 2 00:09:00 Data Preparation - Standardizing Data - Part 1 Data Preparation - Standardizing Data - Part 1 00:07:00 Data Preparation - Standardizing Data - Part 2 Data Preparation - Standardizing Data - Part 2 00:04:00 Data Preparation - Normalizing Data Data Preparation - Normalizing Data 00:08:00 Data Preparation - Binarizing Data Data Preparation - Binarizing Data 00:06:00 Feature Selection - Introduction Feature Selection - Introduction 00:07:00 Feature Selection - Uni-variate Part 1 - Chi-Squared Test Feature Selection - Uni-variate Part 1 - Chi-Squared Test 00:09:00 Feature Selection - Uni-variate Part 2 - Chi-Squared Test Feature Selection - Uni-variate Part 2 - Chi-Squared Test 00:10:00 Feature Selection - Recursive Feature Elimination Feature Selection - Recursive Feature Elimination 00:11:00 Feature Selection - Principal Component Analysis (PCA) Feature Selection - Principal Component Analysis (PCA) 00:09:00 Feature Selection - Feature Importance Feature Selection - Feature Importance 00:07:00 Refresher Session - The Mechanism of Re-sampling, Training and Testing Refresher Session - The Mechanism of Re-sampling, Training and Testing 00:12:00 Algorithm Evaluation Techniques - Introduction Algorithm Evaluation Techniques - Introduction 00:07:00 Algorithm Evaluation Techniques - Train and Test Set Algorithm Evaluation Techniques - Train and Test Set 00:11:00 Algorithm Evaluation Techniques - K-Fold Cross Validation Algorithm Evaluation Techniques - K-Fold Cross Validation 00:09:00 Algorithm Evaluation Techniques - Leave One Out Cross Validation Algorithm Evaluation Techniques - Leave One Out Cross Validation 00:05:00 Algorithm Evaluation Techniques - Repeated Random Test-Train Splits Algorithm Evaluation Techniques - Repeated Random Test-Train Splits 00:07:00 Algorithm Evaluation Metrics - Introduction Algorithm Evaluation Metrics - Introduction 00:09:00 Algorithm Evaluation Metrics - Classification Accuracy Algorithm Evaluation Metrics - Classification Accuracy 00:08:00 Algorithm Evaluation Metrics - Log Loss Algorithm Evaluation Metrics - Log Loss 00:03:00 Algorithm Evaluation Metrics - Area Under ROC Curve Algorithm Evaluation Metrics - Area Under ROC Curve 00:06:00 Algorithm Evaluation Metrics - Confusion Matrix Algorithm Evaluation Metrics - Confusion Matrix 00:10:00 Algorithm Evaluation Metrics - Classification Report Algorithm Evaluation Metrics - Classification Report 00:04:00 Algorithm Evaluation Metrics - Mean Absolute Error - Dataset Introduction Algorithm Evaluation Metrics - Mean Absolute Error - Dataset Introduction 00:06:00 Algorithm Evaluation Metrics - Mean Absolute Error Algorithm Evaluation Metrics - Mean Absolute Error 00:07:00 Algorithm Evaluation Metrics - Mean Square Error Algorithm Evaluation Metrics - Mean Square Error 00:03:00 Algorithm Evaluation Metrics - R Squared Algorithm Evaluation Metrics - R Squared 00:04:00 Classification Algorithm Spot Check - Logistic Regression Classification Algorithm Spot Check - Logistic Regression 00:12:00 Classification Algorithm Spot Check - Linear Discriminant Analysis Classification Algorithm Spot Check - Linear Discriminant Analysis 00:04:00 Classification Algorithm Spot Check - K-Nearest Neighbors Classification Algorithm Spot Check - K-Nearest Neighbors 00:05:00 Classification Algorithm Spot Check - Naive Bayes Classification Algorithm Spot Check - Naive Bayes 00:04:00 Classification Algorithm Spot Check - CART Classification Algorithm Spot Check - CART 00:04:00 Classification Algorithm Spot Check - Support Vector Machines Classification Algorithm Spot Check - Support Vector Machines 00:05:00 Regression Algorithm Spot Check - Linear Regression Regression Algorithm Spot Check - Linear Regression 00:08:00 Regression Algorithm Spot Check - Ridge Regression Regression Algorithm Spot Check - Ridge Regression 00:03:00 Regression Algorithm Spot Check - Lasso Linear Regression Regression Algorithm Spot Check - Lasso Linear Regression 00:03:00 Regression Algorithm Spot Check - Elastic Net Regression Regression Algorithm Spot Check - Elastic Net Regression 00:02:00 Regression Algorithm Spot Check - K-Nearest Neighbors Regression Algorithm Spot Check - K-Nearest Neighbors 00:06:00 Regression Algorithm Spot Check - CART Regression Algorithm Spot Check - CART 00:04:00 Regression Algorithm Spot Check - Support Vector Machines (SVM) Regression Algorithm Spot Check - Support Vector Machines (SVM) 00:04:00 Compare Algorithms - Part 1 : Choosing the best Machine Learning Model Compare Algorithms - Part 1 : Choosing the best Machine Learning Model 00:09:00 Compare Algorithms - Part 2 : Choosing the best Machine Learning Model Compare Algorithms - Part 2 : Choosing the best Machine Learning Model 00:05:00 Pipelines : Data Preparation and Data Modelling Pipelines : Data Preparation and Data Modelling 00:11:00 Pipelines : Feature Selection and Data Modelling Pipelines : Feature Selection and Data Modelling 00:10:00 Performance Improvement: Ensembles - Voting Performance Improvement: Ensembles - Voting 00:07:00 Performance Improvement: Ensembles - Bagging Performance Improvement: Ensembles - Bagging 00:08:00 Performance Improvement: Ensembles - Boosting Performance Improvement: Ensembles - Boosting 00:05:00 Performance Improvement: Parameter Tuning using Grid Search Performance Improvement: Parameter Tuning using Grid Search 00:08:00 Performance Improvement: Parameter Tuning using Random Search Performance Improvement: Parameter Tuning using Random Search 00:06:00 Export, Save and Load Machine Learning Models : Pickle Export, Save and Load Machine Learning Models : Pickle 00:10:00 Export, Save and Load Machine Learning Models : Joblib Export, Save and Load Machine Learning Models : Joblib 00:06:00 Finalizing a Model - Introduction and Steps Finalizing a Model - Introduction and Steps 00:07:00 Finalizing a Classification Model - The Pima Indian Diabetes Dataset Finalizing a Classification Model - The Pima Indian Diabetes Dataset 00:07:00 Quick Session: Imbalanced Data Set - Issue Overview and Steps Quick Session: Imbalanced Data Set - Issue Overview and Steps 00:09:00 Iris Dataset : Finalizing Multi-Class Dataset Iris Dataset : Finalizing Multi-Class Dataset 00:09:00 Finalizing a Regression Model - The Boston Housing Price Dataset Finalizing a Regression Model - The Boston Housing Price Dataset 00:08:00 Real-time Predictions: Using the Pima Indian Diabetes Classification Model Real-time Predictions: Using the Pima Indian Diabetes Classification Model 00:07:00 Real-time Predictions: Using Iris Flowers Multi-Class Classification Dataset Real-time Predictions: Using Iris Flowers Multi-Class Classification Dataset 00:03:00 Real-time Predictions: Using the Boston Housing Regression Model Real-time Predictions: Using the Boston Housing Regression Model 00:08:00 Resources Resources - Python Machine Learning & Data Science Fundamentals 00:00:00