Name: Regression Analysis for Statistics & Machine Learning in R
Price: 135.99 GBP
Availability: InStock

<strong>Learn GitHub Actions in a weekend! This course covers all the important concepts to help you master GitHub Actions and its practical applications. Gain in-demand skills, design a CI/CD pipeline, and deploy infra as code with GitHub Actions. Boost your career with this essential skill for DevOps practices.</strong>
        <p>Workflows are defined by a YAML file checked into your repository and will run when triggered by an event in your repository, or they can be triggered manually, or on a defined schedule. GitHub Actions makes it easy to automate all your software workflows, now with world-class CI/CD. Build, test, and deploy your code right from GitHub. Make code reviews, branch management, and issue triaging work the way you want.

In this intensive course, you will learn the fundamentals of GitHub Actions workflow in a compact timeframe. The course covers important concepts such as the workflow structure and components, events, jobs, steps, and runners. It also dives into various topics such as environment variables, GitHub variables, secure password storage, and manual approvals.

Additionally, the course teaches techniques for sharing values between steps and jobs and explains the use of self-hosted runners. The course concludes with a demonstration of preparing an infrastructure as code (IAC) template with Bicep and deploying it through a GitHub Action workflow. The course will equip you with the skills to automate your entire software workflow using GitHub Actions, from idea to production.

By the end of this course, you will have a solid understanding of how to use GitHub Actions to automate your software workflows.

All the resource files are added to the GitHub repository at: https://github.com/PacktPublishing/Learning-GitHub-Actions-for-DevOps-CI-CD</p>
        <h2>What You Will Learn</h2><p>Understand GitHub Action workflow basics<br>Learn about workflow components (event, job, step, runner)<br>Add a self-hosted runner and execute jobs using it<br>Design an IAC template with Bicep to deploy infrastructures<br>Build, push, and deploy Docker containers<br>Deploy a container to the Azure web app for optimal performance</p>
        <h2>Audience</h2><p>This course is designed for cloud consultants who work on platform automation requirements or those who want to experience the power of Azure Serverless Computing.<br><br>Azure IAAS and PAAS administrators, application developers, and cloud computing enthusiasts will also gain a lot from this course.<br><br>To get the most out of this course, you should know about YAML file syntax; some basic understanding of the command line (Win CMD/Unix Shell) will help you quickly grasp the concepts; and Visual Studio Code should be installed on your laptop.</p>
        <h2>Approach</h2><p>This is a concise, easy-to-understand, to-the-point, and well-balanced course on GitHub Actions from scratch. You will look at the basic concepts at the beginning, followed by some advanced topics. With a focus on practical examples and hands-on experience, you will learn how to build, push, and deploy Docker containers with ease.</p>
        <h2>Key Features</h2><p>Get ready to delve into the intricacies of Git workflow in a well-structured and easy-to-understand format * This course is jam-packed with valuable resources, including templates, resource files, and PPTs to enhance your learning experience * A beginner-friendly course on GitHub Actions and related operations, designed to equip you with the latest tools from the ground up</p>
        <h2>Github Repo</h2><p>https://github.com/PacktPublishing/Learning-GitHub-Actions-for-DevOps-CI-CD</p>
        <h2>About the Author</h2><h3>Vijay Saini</h3><p>Vijay Saini is an accomplished IT professional who brings a wealth of expertise to the table. With a diversified background across multiple domains, Vijay has proven himself a valuable asset to his current role as a leading cloud service provider. His strong focus on automation has resulted in significant cost savings for the business, making him a valuable asset to the team.

Vijay is highly knowledgeable in the areas of Microsoft Azure, cloud technologies, DBMS, and Python, and is a specialist in automation using PowerShell. With a passion for teaching, Vijay has leveraged e-learning platforms to share his expertise with others, helping them develop their own skills and knowledge.</p>
        <h2>Course Outline</h2><h4>1. Introduction to the GitHub Action Workflows</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Overview of GitHub Action Workflow</p><p style='margin: 0'>This video provides an overview of the GitHub Action workflow.</p></td></tr><tr><td style='padding: 15px;'><p>2. Exploring Workflow Components - Events</p><p style='margin: 0'>This video helps in exploring workflow components; here, you will be focusing on events.</p></td></tr><tr><td style='padding: 15px;'><p>3. Exploring Workflow Components - Job, Step, and Runner</p><p style='margin: 0'>This video helps in exploring workflow components; here, you will be focusing on job, step, and runner.</p></td></tr><tr><td style='padding: 15px;'><p>4. Running the Workflow and Reading the Logs</p><p style='margin: 0'>This video helps you with running the workflow and reading the logs.</p></td></tr></tbody></table><br><h4>2. GitHub Actions: Exploring the Features</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Environment Variables</p><p style='margin: 0'>This video explains environment variables in detail. Here, you will look at different ways of creating variables and using their values inside our workflows.</p></td></tr><tr><td style='padding: 15px;'><p>2. Default GitHub Variables</p><p style='margin: 0'>This video explains the default GitHub variables and its use cases.</p></td></tr><tr><td style='padding: 15px;'><p>3. GitHub Actions Store Your Secrets and Passwords Securely</p><p style='margin: 0'>This video demonstrates how GitHub Actions store your secrets and passwords securely.</p></td></tr><tr><td style='padding: 15px;'><p>4. GitHub_Artifacts</p><p style='margin: 0'>This video explains in-depth about GitHub_Artifacts.</p></td></tr><tr><td style='padding: 15px;'><p>5. GitHub Environments | How to Add Manual Approvals</p><p style='margin: 0'>This video demonstrates GitHub environments, and you will focus on how to add manual approvals.</p></td></tr><tr><td style='padding: 15px;'><p>6. Sharing Values Between Steps and Jobs in a Workflow</p><p style='margin: 0'>This video demonstrates how to share the values between steps and jobs in a workflow.</p></td></tr></tbody></table><br><h4>3. GitHub Runners</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. What Is a GitHub Runner</p><p style='margin: 0'>This video provides an introduction to the GitHub runner.</p></td></tr><tr><td style='padding: 15px;'><p>2. Adding a Self-Hosted Runner</p><p style='margin: 0'>This video demonstrates how to add a self-hosted runner.</p></td></tr><tr><td style='padding: 15px;'><p>3. Running Jobs on Self-Hosted Runner</p><p style='margin: 0'>This video explains and demonstrates running jobs on a self-hosted runner.</p></td></tr></tbody></table><br><h4>4. GitHub Actions for Infrastructure Deployment</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Understanding the Need of Infrastructure as Code</p><p style='margin: 0'>This video helps in understanding the need of Infrastructure as Code (IaC).</p></td></tr><tr><td style='padding: 15px;'><p>2. Developing IAC Template with Bicep to Deploy Infrastructure - Part 1</p><p style='margin: 0'>This is the first of the two-part video where you will develop and deploy an IAC template with Bicep in order to automate infrastructural deployment for specific requirements. These specific requirements are resources such as Storage Account, Container Registry, and Service Bus Namespace.</p></td></tr><tr><td style='padding: 15px;'><p>3. Developing IAC Template with Bicep to Deploy Infrastructure - Part 2</p><p style='margin: 0'>This is the second of the two-part video where you will develop and deploy an IAC template with Bicep in order to automate infrastructural deployment for specific requirements. These specific requirements are resources such as App Service Plan and Web App.</p></td></tr><tr><td style='padding: 15px;'><p>4. Setting Up Authentication</p><p style='margin: 0'>This video helps in setting up authentication.</p></td></tr><tr><td style='padding: 15px;'><p>5. Developing GitHub Actions Workflow for Infra Deployment - Part 1</p><p style='margin: 0'>This is the first of the two-part video where you will develop a GitHub Actions workflow that will use this authentication information to connect with Azure subscription and then deploy the template to a resource group in order to automate end-to-end infrastructure deployment.</p></td></tr><tr><td style='padding: 15px;'><p>6. Developing GitHub Actions Workflow for Infra Deployment - Part 2</p><p style='margin: 0'>This is the second of the two-part video where you will update/enhance the code file, then push it to the repository and test it right away.</p></td></tr></tbody></table><br><h4>5. Continuous Integration and Continuous Deployment</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Continuous Integration</p><p style='margin: 0'>This video explains Continuous Integration (CI) from scratch.</p></td></tr><tr><td style='padding: 15px;'><p>2. Continuous Deployment Workflow to Deploy to Azure App Service</p><p style='margin: 0'>This video explains Continuous Deployment (CD) workflow and you will use it to deploy to Azure App Service.</p></td></tr></tbody></table><br><h4>6. Building, Pushing, and Deploying Docker Containers</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Building Dockers with GitHub Actions</p><p style='margin: 0'>This video covers the process of building Docker containers using GitHub Actions.</p></td></tr><tr><td style='padding: 15px;'><p>2. Deploying Dockers with GitHub Actions</p><p style='margin: 0'>Learn how to deploy Docker containers using GitHub Actions in this video tutorial.</p></td></tr></tbody></table>

Packt

Java

DevOps

GitHub

Learn GitHub Actions in a weekend! This course covers all the important concepts to help you master GitHub Actions and its practical applications. Gain in-demand skills, design a CI/CD pipeline, and deploy infra as code with GitHub Actions. Boost your career with this essential skill for DevOps practices.

Learning GitHub Actions for DevOps CI/CD

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<h2 fr-original-style="" style="box-sizing: border-box;">Business Intelligence Analyst Course Overview</h2></div>
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<p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Did you know that businesses harnessing the power of Business Intelligence (BI) in the UK alone are 23% more likely to outperform their competition? In today&#39;s data-driven world, the key to success lies in making informed decisions, and that&#39;s where our Business Intelligence Analyst Course comes in!</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">This course will help you master reporting, analytics, data mining, benchmarking, and complex event processing, enabling you to make data-driven decisions that can transform your business. As a business owner or aspiring business analyst, you&#39;ll gain the ability to implement BI strategies that drive success for large companies in this Business Intelligence Analyst Course course. Plus, you will become a pro at choosing the exemplary RTBI architecture to achieve the best results in various sectors. As you move deeper into the Business Intelligence Analyst Course course, you will gain insights into business statistics, data science, and different analytics types to give you a well-rounded skill set.&nbsp;</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">SQL expertise is a must-have for data management, and our course ensures you&#39;re not just familiar with it but a true SQL wizard, versed in different data types. Furthermore, this Business Intelligence Analyst Course will teach you the essentials of database management and help you grasp data warehouse concepts to effectively manage your organization&#39;s data. Before the end, the course will provide you with in-depth knowledge of data visualization in business intelligence and the basics of Python programming to enhance your ability to convey critical information and perform advanced data analysis.</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Make a smart choice for your future. Eneol in our Business Intelligence Analyst Course to excel in the business field. </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;"><span style="font-size: 18px; box-sizing: border-box;" fr-original-style="font-size: 18px;">Business Intelligence Analyst Course Curriculum&nbsp;<br fr-original-style="" style="box-sizing: border-box;"></span></strong></p><ul fr-original-style="" style="box-sizing: border-box;"><li fr-original-style="" style="box-sizing: border-box;">Module-1: An Introduction to Business Intelligence</li><li fr-original-style="" style="box-sizing: border-box;">Module-2: Real-time Business Intelligence</li><li fr-original-style="" style="box-sizing: border-box;">Module-3: Fundamentals of Statistics and Data Science</li><li fr-original-style="" style="box-sizing: border-box;">Module-4: Fundamentals of SQL</li><li fr-original-style="" style="box-sizing: border-box;">Module-5: Database Management Essentials</li><li fr-original-style="" style="box-sizing: border-box;">Module-6: Data Warehouse Concepts</li><li fr-original-style="" style="box-sizing: border-box;">Module-7: Data Visualisation in Business Intelligence</li><li fr-original-style="" style="box-sizing: border-box;">Module-8: Basics of Python</li></ul></div><span style="font-size: 18px; box-sizing: border-box;" fr-original-style="font-size: 18px;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">
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</span></strong><h3 fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Why Choose Teachers Training</strong></h3></div>
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<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;">CPD Certification from The Teachers Training</strong></p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Successfully completing the MCQ exam of this course qualifies you for a CPD-accredited certificate from The Teachers Training. You will be eligible for both PDF copy and hard copy of the certificate to showcase your achievement however you wish.</p><ul fr-original-style="" style="box-sizing: border-box;"><li fr-original-style="" style="box-sizing: border-box;">You can get your digital certificate (PDF) for &pound;4.99 only</li><li fr-original-style="" style="box-sizing: border-box;">Hard copy certificates are also available, and you can get one for only &pound;10.99</li><li fr-original-style="" style="box-sizing: border-box;">You can get both PDF and Hard copy certificates for just &pound;12.99!</li></ul><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">The certificate will add significant weight to your CV and will give you a competitive advantage when applying for jobs.</p></div>
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The Teachers Training

Business Development

Unlock the potential of business intelligence with our specialized Business Intelligence Analyst Course. Learn to analyze data, extract insights, and drive strategic decisions to optimize business performance. Gain practical skills in data visualization, reporting, and predictive analytics using industry-leading tools and techniques. Whether you're a business professional or aspiring analyst, this course equips you with the expertise to excel in leveraging data for business intelligence.

Business Intelligence Analyst Course

<strong>Learn to build a custom object-oriented PHP MVC framework and application</strong>
        <p>In this course, we will go step-by-step to build a complete custom MVC (Model View Controller) framework called TraversyMVC using object-oriented PHP. We will build something like CodeIgniter, but much lighter. This framework is completely open source, and you are free to change the name, add elements, and use it as your own in your own projects.

This framework will include: -
&bull;	A core library class to load controllers and methods from the URL (also using .htaccess).
&bull;	A base controller class to load models and views.
&bull;	A custom database library using PDO for all models to interact with the database using prepared statements.

We will not only create the framework but will build an application on top of it called SharePosts which will comprise something akin to a social network to share posts. This application will include: -
&bull;	Full user authentication 
&bull;	Access control for posts 
&bull;	Server-side form validation 
&bull;	Bootstrap 4 UI 
&bull;	Posts CRUD 
&bull;	Helper functions (flash messaging and redirects)

We will also deploy the application to the Internet. This is not a beginner PHP course. To learn the basics, please check out the PHP Front-To-Back series by Traversy Media.

All the code and supporting files for this course are available at - https://github.com/PacktPublishing/Object-Oriented-PHP-and-MVC</p>
        <h2>What You Will Learn</h2><p>Build a custom MVC Framework entirely from scratch<br>Build an application using your custom framework<br>Create a custom PDO class to handle database interactions<br>Complete user authentication using OOP and PDO<br>Deploy your custom PHP application</p>
        <h2>Audience</h2><p>This course is for people who want to learn advanced OOP PHP and MVC (Model View Controller) with basic knowledge of PHP and programming concepts.</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>The course is constructed to explain the fundamental principles required to build a customized framework with object-oriented PHP. * Clear, precise and thorough methodologies are used to explain the concepts and take you through the process of building the application</p>
        <h2>Github Repo</h2><p>https://github.com/packtpublishing/object-oriented-php-and-mvc</p>
        <h2>About the Author</h2><h3>Brad Traversy</h3><p>Brad Traversy has been programming for around 12 years and teaching for almost 5 years. He is the owner of Traversy Media, which is a successful web development YouTube channel and specializes in everything from HTML5 to front-end frameworks such as Angular as well as server-side technologies such as Node.js, PHP, and Python. Brad has mastered explaining overly complex topics in a simple manner that is understandable. Invest in your knowledge by watching Brad's courses.</p>
        <h2>Course Outline</h2><h4>1. Course Intro & Setup</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Welcome To the Course</p><p style='margin: 0'>Course Intro &amp; Setup: Welcome To the Course</p></td></tr><tr><td style='padding: 15px;'><p>2. Project Files & Questions</p><p style='margin: 0'>Course Intro &amp; Setup: Project Files &amp; Questions</p></td></tr><tr><td style='padding: 15px;'><p>3. XAMPP Environment Setup</p><p style='margin: 0'>Course Intro &amp; Setup: XAMPP Environment Setup</p></td></tr></tbody></table><br><h4>2. Intro to OOP PHP</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. About This Section</p><p style='margin: 0'>Intro to OOP PHP: About This Section</p></td></tr><tr><td style='padding: 15px;'><p>2. What Is OOP?</p><p style='margin: 0'>Intro to OOP PHP: What Is OOP?</p></td></tr><tr><td style='padding: 15px;'><p>3. Classes, Properties & Methods</p><p style='margin: 0'>Intro to OOP PHP: Classes, Properties &amp; Methods</p></td></tr><tr><td style='padding: 15px;'><p>4. The Constructor & Destructor</p><p style='margin: 0'>Intro to OOP PHP: The Constructor &amp; Destructor</p></td></tr><tr><td style='padding: 15px;'><p>5. Access Modifiers, Getters & Setters</p><p style='margin: 0'>Intro to OOP PHP: Access Modifiers, Getters &amp; Setters</p></td></tr><tr><td style='padding: 15px;'><p>6. Class Inheritance</p><p style='margin: 0'>Intro to OOP PHP: Class Inheritance</p></td></tr><tr><td style='padding: 15px;'><p>7. Static Methods & Properties</p><p style='margin: 0'>Intro to OOP PHP: Static Methods &amp; Properties</p></td></tr></tbody></table><br><h4>3. The Framework [Part 1] - The Core</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. What Is MVC?</p><p style='margin: 0'>The Framework [Part 1] - The Core: What Is MVC?</p></td></tr><tr><td style='padding: 15px;'><p>2. Workflow Explanation</p><p style='margin: 0'>The Framework [Part 1] - The Core: Workflow Explanation</p></td></tr><tr><td style='padding: 15px;'><p>3. Creating the Folder Structure</p><p style='margin: 0'>The Framework [Part 1] - The Core: Creating the Folder Structure</p></td></tr><tr><td style='padding: 15px;'><p>4. Direct Everything Through index.php</p><p style='margin: 0'>The Framework [Part 1] - The Core: Direct Everything Through index.php</p></td></tr><tr><td style='padding: 15px;'><p>5. Bootstrap File & Core Class</p><p style='margin: 0'>The Framework [Part 1] - The Core: Bootstrap File &amp; Core Class</p></td></tr><tr><td style='padding: 15px;'><p>6. Loading the Controller from the URL</p><p style='margin: 0'>The Framework [Part 1] - The Core: Loading the Controller from the URL</p></td></tr><tr><td style='padding: 15px;'><p>7. Mapping Methods & Parameters</p><p style='margin: 0'>The Framework [Part 1] - The Core: Mapping Methods &amp; Parameters</p></td></tr></tbody></table><br><h4>4. The Framework [Part 2] - MVC Workflow</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Base Controller Class</p><p style='margin: 0'>The Framework [Part 2] - MVC Workflow: Base Controller Class</p></td></tr><tr><td style='padding: 15px;'><p>2. Loading Views</p><p style='margin: 0'>The Framework [Part 2] - MVC Workflow: Loading Views</p></td></tr><tr><td style='padding: 15px;'><p>3. Config File & Uploader</p><p style='margin: 0'>The Framework [Part 2] - MVC Workflow: Config File &amp; Uploader</p></td></tr><tr><td style='padding: 15px;'><p>4. Header & Footer Includes</p><p style='margin: 0'>The Framework [Part 2] - MVC Workflow: Header &amp; Footer Includes</p></td></tr><tr><td style='padding: 15px;'><p>5. Aside - PDO Crash Course</p><p style='margin: 0'>The Framework [Part 2] - MVC Workflow: Aside - PDO Crash Course</p></td></tr><tr><td style='padding: 15px;'><p>6. The Database Class - Part 1</p><p style='margin: 0'>The Framework [Part 2] - MVC Workflow: The Database Class - Part 1</p></td></tr><tr><td style='padding: 15px;'><p>7. The Database Class - Part 2</p><p style='margin: 0'>The Framework [Part 2] - MVC Workflow: The Database Class - Part 2</p></td></tr><tr><td style='padding: 15px;'><p>8. Clean Up</p><p style='margin: 0'>The Framework [Part 2] - MVC Workflow: Clean Up</p></td></tr></tbody></table><br><h4>5. The App [1] - Setup & User Authentication</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Initial App & Database Setup</p><p style='margin: 0'>The App [1] - Setup &amp; User Authentication: Initial App &amp; Database Setup</p></td></tr><tr><td style='padding: 15px;'><p>2. Pages, Bootstrap & Navbar</p><p style='margin: 0'>The App [1] - Setup &amp; User Authentication: Pages, Bootstrap &amp; Navbar</p></td></tr><tr><td style='padding: 15px;'><p>3. Creating the Users Controller</p><p style='margin: 0'>The App [1] - Setup &amp; User Authentication: Creating the Users Controller</p></td></tr><tr><td style='padding: 15px;'><p>4. Register & Login Form Views</p><p style='margin: 0'>The App [1] - Setup &amp; User Authentication: Register &amp; Login Form Views</p></td></tr><tr><td style='padding: 15px;'><p>5. Form Validation</p><p style='margin: 0'>The App [1] - Setup &amp; User Authentication: Form Validation</p></td></tr><tr><td style='padding: 15px;'><p>6. User Model & Email Check</p><p style='margin: 0'>The App [1] - Setup &amp; User Authentication: User Model &amp; Email Check</p></td></tr><tr><td style='padding: 15px;'><p>7. User Registration</p><p style='margin: 0'>The App [1] - Setup &amp; User Authentication: User Registration</p></td></tr><tr><td style='padding: 15px;'><p>8. Custom Flash Messaging</p><p style='margin: 0'>The App [1] - Setup &amp; User Authentication: Custom Flash Messaging</p></td></tr><tr><td style='padding: 15px;'><p>9. User Login</p><p style='margin: 0'>The App [1] - Setup &amp; User Authentication: User Login</p></td></tr><tr><td style='padding: 15px;'><p>10. User Session Data & Logout</p><p style='margin: 0'>The App [1] - Setup &amp; User Authentication: User Session Data &amp; Logout</p></td></tr></tbody></table><br><h4>6. The App [2] - Posts Functionality</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Posts Controller</p><p style='margin: 0'>The App [2] - Posts Functionality: Posts Controller</p></td></tr><tr><td style='padding: 15px;'><p>2. Posts Access Control</p><p style='margin: 0'>The App [2] - Posts Functionality: Posts Access Control</p></td></tr><tr><td style='padding: 15px;'><p>3. Post Model & Display</p><p style='margin: 0'>The App [2] - Posts Functionality: Post Model &amp; Display</p></td></tr><tr><td style='padding: 15px;'><p>4. Add Post Form</p><p style='margin: 0'>The App [2] - Posts Functionality: Add Post Form</p></td></tr><tr><td style='padding: 15px;'><p>5. Inserting Posts</p><p style='margin: 0'>The App [2] - Posts Functionality: Inserting Posts</p></td></tr><tr><td style='padding: 15px;'><p>6. Post Show Details Page</p><p style='margin: 0'>The App [2] - Posts Functionality: Post Show Details Page</p></td></tr><tr><td style='padding: 15px;'><p>7. Editing Posts</p><p style='margin: 0'>The App [2] - Posts Functionality: Editing Posts</p></td></tr><tr><td style='padding: 15px;'><p>8. Deleting Posts</p><p style='margin: 0'>The App [2] - Posts Functionality: Deleting Posts</p></td></tr></tbody></table><br><h4>7. App Deployment</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Deploying Our App</p><p style='margin: 0'>App Deployment: Deploying Our App</p></td></tr></tbody></table>

Programming

Learn to build a custom object-oriented PHP MVC framework and application

Object Oriented PHP and MVC

<p>Become a worldwide competitor with skills that are validated for quality by QLS, the most respected high-quality course auditor in the UK.</p><p>This premium QLS endorsed Learn Ethical Hacking From A-Z: Beginner To Expert course comes with intensive study modules, dedicated tutor assistance, customer support, flexible learning opportunity and a globally recognised certification all-together. Because QLS-endorsed courses have a high perceived value, finishing our Learn Ethical Hacking From A-Z: Beginner To Expert course will open up countless chances for you to pursue wherever in the world!</p><p>Furthermore, neither we nor you will compromise on the exceptional quality of our first-rate education. This amazing Learn Ethical Hacking From A-Z: Beginner To Expert course will teach you the most comprehensive content possible, opening up a world of opportunity for you to seize and succeed in. This course is really an incredible deal, especially considering the price! You should definitely not pass up this investment!</p><p>So, why delay any longer? Benefit your career progression by joining us today and distinguish yourself as, unquestionably, the most skilled one in your workplace!</p><p><strong>Why Learn with us: </strong></p><p>We, as one of the leading eLearning service providers across the globe, strive to provide all our learners with the best eLearning experience possible that can make a real difference in their career progression.</p><p><strong>Our Service for the </strong><strong>Learn Ethical Hacking From A-Z: Beginner To Expert</strong><strong> Includes: </strong></p><ul><li>Intensive Study Notes</li><li>Tutor Support</li><li>Customer Support</li><li>Assignment Help</li><li>QLS Endorsed Certificate</li><li>24/7 Learning Portal Access</li><li>Widely Compatible Study Materials</li></ul><p><strong>Course Curriculum of </strong><strong>Learn Ethical Hacking From A-Z: Beginner To Expert</strong></p><ul><li>Course Introduction</li><li>Networking Basics</li><li>Setting Up Your Hacking Lab</li><li>Linux/Python/Bash &amp; PowerShell Basics</li><li>How To Remain Anonymous On The Web</li><li>How To Hack Into WIFI</li><li>Passive &amp; Active Reconnaissance (Information Gathering)</li><li>Launching Attacks</li><li>Post Exploitation</li><li>Website &amp; Web Application Hacking</li><li>Mobile Phone Hacking &amp; Security</li><li>Getting Your Name Out There As An Ethical Hacker</li><li>How To Make Money As An Ethical Hacker</li><li>How To Start A Career In Cybersecurity</li></ul><p><strong>Assessment &amp; Certification</strong></p><p>Learners must submit a comprehensive summerised assignment on all the units that will be assessed by our expert tutor if all the learning outcomes are met as per the standard set by QLS. After the quality check, learner will be provided with the Learn Ethical Hacking From A-Z: Beginner To Expert certificate.</p><p><strong>Endorsed Certificate of Achievement from the Quality Licence Scheme</strong></p><p>An endorsed certificate will be issued to learners at the end of the course as recognition of course completion. Provided that learner completes all the assessment of a course can claim for certificate.</p><p><strong>Endorsement:</strong></p><p>QLS endorsed this certified course as a highly qualified, non-regulated provision and training programme. There will be a trainer to answer all your questions including your progression routes into further higher education.</p><h2>
        
        <div>CPD</div>
    </h2>

                        <div id="cpd">
                            <div>
                                <div>
                                    <div>
                                        15 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>We welcome all students to our course. This Learn Ethical Hacking From A-Z: Beginner To Expert course is perfect for anyone who want to become proficient in the field and have the information and skills necessary to enter it as a promising new venture.</p>
                        </div><h2>
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                            <p>This course, Learn Ethical Hacking From A-Z: Beginner To Expert, does not require any formal prerequisites. Therefore, there are no prerequisites for students to join in this course.</p>
                        </div><h2>
        
        <div>Certificates</div>
    </h2>

                        <div id="optional_extras">
                                    <h4>Advanced Diploma in Ethical Hacking From A-Z Beginner To Expert at QLS Level 7</h4>
        <p>
            Hard copy certificate -
            £75
        </p>

                        </div>

Kingston Open College

Certified Cryptocurrency Investigator Course (CCI)

Certificate in Further Education & Training (Cert Ed)

Certified Ethical Hacker (CEH)

ICDL (International Certification of Digital Literacy)

Ethical Hacking

QLS Endorsed + CPD QS Accredited - Dual Certification | Instant Access | 24/7 Tutor Support

Diploma in Learn Ethical Hacking From A-Z: Beginner To Expert - Level 7 (QLS Endorsed)

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			<h2>Overview
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					<p><span>This comprehensive course on </span><b><span>Business Intelligence Analyst Course</span></b> will deepen your understanding on this topic.</p><p><span><span>After successful completion of this course you can acquire the required skills in this sector. This </span><b>Business Intelligence Analyst Course</b> comes with accredited certification from CPD, which will enhance your CV and make you worthy in the job market.</span></p><p><span><span>So enrol in this course today to fast track your career ladder.</span></span></p>					</div>
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			<h2>How will I get my certificate?</h2>		</div>
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					<p>You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate.</p>					</div>
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			<h2>Who is This course for?</h2>		</div>
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					<p><span>There is no experience or previous qualifications required for enrolment on this </span><b><span>Business Intelligence Analyst Course</span></b>. It is available to all students, of all academic backgrounds.</p>					</div>
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			<h2>Requirements</h2>		</div>
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					<p><span>Our </span><b><span>Business Intelligence Analyst Course</span></b> is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G.</p><p><span><span>There is no time limit for completing this course, it can be studied in your own time at your own pace.</span></span></p>					</div>
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			<h2>Career Path</h2>		</div>
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					<p>Learning this new skill will help you to advance in your career. It will diversify your job options and help you develop new techniques to keep up with the fast-changing world. This skillset will help you to-</p><ul><li>Open doors of opportunities</li><li>Increase your adaptability</li><li>Keep you relevant</li><li>Boost confidence</li></ul><p>And much more!</p>					</div>
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					</div> <h3>Course Curriculum</h3><div><p>8 sections • 8 lectures • 05:21:00 total length</p></div><div><div><div><div><div><div><div><p>•An Introduction to Business Intelligence: 00:46:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Real-time Business Intelligence: 00:35:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Fundamentals of Statistics and Data Science: 00:50:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Fundamentals of SQL: 00:40:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Database Management Essentials: 00:50:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Data Warehouse Concepts: 00:38:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Data Visualisation in Business Intelligence: 00:35:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Basics of Python: 00:27:00</p></div></div></div></div></div></div></div></div></div></div></div></div></div></div>

Apex Learning

Business Analyst

Business Analysis

Business Analytics & Intelligence

Oracle Business Intelligence

Business Intelligence (BI)

Business Data Analysis

<strong>Welcome to this project-based course where you will build and deploy a realtor clone application using the latest version of React, Firebase, and Tailwind CSS. Learn to create and deploy a website professionally for showcasing to friends and clients, or adding it to your portfolio. Basic knowledge of HTML, CSS, and JavaScript is expected.</strong>
        <p>This is the best course to learn React.js, Firebase, and Tailwind CSS by creating a real estate website. In this course, you are going to learn how to build a realtor clone using ReactJS version 18, Firebase version 9, and Tailwind CSS version 3. 

In this course, we are going to create a stunning new listing section, custom categories, responsive design, listing cards, rent and sale pages, and, most importantly, listing pages where you can see the map and image slider. Realtor clone is the best modern fully functional real estate application that you can currently find. By building this single web app, you will gain the knowledge needed to build any website that uses CRUD operations including CRUD functions in React using Firebase Firestore database. 

You will learn Firebase auth for complete authentication and learn how to sign up or sign in the users using username and password and Google oAuth. Also, we will add the Forgot Password functionality using Firebase auth to let the users get an email with the link to change their password. You will learn how to style the project using Tailwind CSS, including how to add custom classes. And finally, we will deploy the website to Vercel to be able to share it with others or put it on your portfolio. 

By the end of the course, you will learn to build a realtor clone using ReactJS version 18, Firebase version 9, and Tailwind CSS version 3. 

All resources and code files are placed here: https://github.com/PacktPublishing/React.js-and-Firebase-Project---ReactJS-18-Firebase-9-Project</p>
        <h2>What You Will Learn</h2><p>Create a ReactJS project from scratch<br>Use Firebase Firestore to store and fetch data<br>Learn how to create pages and routes in a React project<br>Learn how to create a beautiful spinner and loader<br>Create a reusable component such as listing cards<br>Learn to create private route and custom hook for protecting the user profile page</p>
        <h2>Audience</h2><p>This course can be taken by React developers who want to have a portfolio project or by programmers who have a basic knowledge of HTML, CSS, and JavaScript.</p>
        <h2>Approach</h2><p>This is a complete hands-on course where you will be creating a website clone from scratch.</p>
        <h2>Key Features</h2><p>Learn React Router version 6 (latest version) to create routes, get the params, and redirect * Learn CRUD operations including create, read, update, and delete using Firebase Firestore * Learn Google Geolocation API and how to convert an address to latitude and longitude</p>
        <h2>Github Repo</h2><p>https://github.com/PacktPublishing/React.js-and-Firebase-Project---ReactJS-18-Firebase-9-Project</p>
        <h2>About the Author</h2><h3>Dr. Sahand Ghavidel </h3><p>Sahand Ghavidel, with degrees in Mathematics, Electrical, and Computer Science, earned his doctorate from the University of Technology Sydney. He has over ten years of research experience in artificial algorithms and optimization, earning multiple awards and publishing 40+ articles in ISI journals. He's also a renowned presenter at global conferences.

Sahand's work, with 1600+ citations on Google Scholar, reflects his significant impact. He was honored as an outstanding reviewer by the "International Journal of Electrical Power & Energy Systems" for his quality contributions.

A programmer since 12, Sahand has 15 years of experience and has created numerous websites and apps, mastering languages like JavaScript and Python.</p>
        <h2>Course Outline</h2><h4>1. Introduction</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Introduction</p><p style='margin: 0'>This video is a brief introduction to the course, what to expect out of the course, and the course prerequisites.</p></td></tr></tbody></table><br><h4>2. Installation and First Template</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Install ReactJS and Tailwind CSS and Create the First Template</p><p style='margin: 0'>This video explains the installation of ReactJS and Tailwind CSS and shows how to create the first template of the project.</p></td></tr><tr><td style='padding: 15px;'><p>2. Create Pages and Routes</p><p style='margin: 0'>This video explains how to create the pages and routes for the project.</p></td></tr><tr><td style='padding: 15px;'><p>3. Create the Header Component</p><p style='margin: 0'>This video explains how to create the header component of the project, the navbar.</p></td></tr></tbody></table><br><h4>3. Authentication Using Firebase Auth Version 9</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Create Sign In, Sign Up, and Forgot Password Pages and OAuth Component</p><p style='margin: 0'>This video explains how to create sign in, sign up, and Forgot Password pages.</p></td></tr><tr><td style='padding: 15px;'><p>2. Install Firebase and react-toastify and Sign Up the User</p><p style='margin: 0'>This video explains the installation process of Firebase and how to sign up the user.</p></td></tr><tr><td style='padding: 15px;'><p>3. Complete the OAuth Functionality</p><p style='margin: 0'>This video explains the OAuth functionality in detail.</p></td></tr><tr><td style='padding: 15px;'><p>4. Complete the Sign-In Functionality</p><p style='margin: 0'>This video explains the sign-in functionality in detail.</p></td></tr><tr><td style='padding: 15px;'><p>5. Complete the Forgot Password Page Functionality</p><p style='margin: 0'>This video explains how to create the Forgot Password page functionality.</p></td></tr></tbody></table><br><h4>4. Profile Page</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Create Private Route for Protecting the Profile Page and Logout Functionality</p><p style='margin: 0'>This video explains how to create a private route for protecting the profile page and the logout functionality.</p></td></tr><tr><td style='padding: 15px;'><p>2. Add the Edit Functionality to the Profile Page</p><p style='margin: 0'>This video explains how to add the edit functionality to the profile page.</p></td></tr><tr><td style='padding: 15px;'><p>3. Complete the Header Component and Make It Dynamic</p><p style='margin: 0'>This video explains how to make the header component of the project dynamic.</p></td></tr><tr><td style='padding: 15px;'><p>4. Create the Spinner Component</p><p style='margin: 0'>This video explains how to create the spinner component.</p></td></tr><tr><td style='padding: 15px;'><p>5. Create the Create Listing Page UI</p><p style='margin: 0'>This video explains how to create the listing page UI.</p></td></tr><tr><td style='padding: 15px;'><p>6. Add Functionality of onchange and onsubmit Functions to the Create Listing Page</p><p style='margin: 0'>This video explains how to add the functionality of onchange and onsubmit functions to the create listing page.</p></td></tr><tr><td style='padding: 15px;'><p>7. Add My Listings Section to the Profile Page and Create the listingItem Component</p><p style='margin: 0'>This video explains how to add my listings section to the profile page and create the listingItem component.</p></td></tr><tr><td style='padding: 15px;'><p>8. Complete the listingItem Component</p><p style='margin: 0'>This video explains the listingItem component.</p></td></tr><tr><td style='padding: 15px;'><p>9. Add Delete and Edit Functionality to the My Listing Section</p><p style='margin: 0'>This video explains how to add the delete and edit functionality to the my listing section.</p></td></tr><tr><td style='padding: 15px;'><p>10. Create EditListing Page</p><p style='margin: 0'>This video explains how to create the EditListing page.</p></td></tr></tbody></table><br><h4>5. Listing Page</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Create Listing Page and Use Swiper to Add the Image Slider</p><p style='margin: 0'>This video explains the listing page and how to use Swiper to add the image slider.</p></td></tr><tr><td style='padding: 15px;'><p>2. Add Share Copy Functionality</p><p style='margin: 0'>This video explains how to add the share copy functionality.</p></td></tr><tr><td style='padding: 15px;'><p>3. Add the Listing Information to the Listing Page</p><p style='margin: 0'>This video explains how to add the listing information to the listing page.</p></td></tr><tr><td style='padding: 15px;'><p>4. Create the Landlord Contact Component</p><p style='margin: 0'>This video explains how to create the landlord contact component.</p></td></tr><tr><td style='padding: 15px;'><p>5. Add Map to the Listing Page Using Leaflet and react-leaflet Packages</p><p style='margin: 0'>This video explains how to add a map to the listing page using leaflet and react-leaflet packages.</p></td></tr></tbody></table><br><h4>6. Homepage</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Create Slider Component and Add It to the Homepage</p><p style='margin: 0'>This video explains how to create a slider component and add it to the homepage of the project.</p></td></tr><tr><td style='padding: 15px;'><p>2. Complete Homepage By Adding Recent Offers, Places for Rent, and Places for Sale</p><p style='margin: 0'>This video completes the homepage by adding recent offers, places for rent, and places for sale.</p></td></tr></tbody></table><br><h4>7. Offers and Category Pages</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Complete the Offers Page</p><p style='margin: 0'>This video explains how to fetch data for the offers page.</p></td></tr><tr><td style='padding: 15px;'><p>2. Create the Places for Rent and Sale Pages</p><p style='margin: 0'>This video explains the code for rent and sale pages of the projects.</p></td></tr></tbody></table><br><h4>8. Deployment</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Deploy to Vercel</p><p style='margin: 0'>This video explains how to deploy the website that we have created to Vercel.</p></td></tr></tbody></table>

JavaScript

Tailwind CSS

Web Development

Welcome to this project-based course where you will build and deploy a realtor clone application using the latest version of React, Firebase, and Tailwind CSS. Learn to create and deploy a website professionally for showcasing to friends and clients, or adding it to your portfolio. Basic knowledge of HTML, CSS, and JavaScript is expected.

ReactJS 18, Firebase 9 Project- Realtor Clone

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					<div><p>Gain the skills and credentials to kickstart a successful career and learn from the experts with this step-by-step training course. This Penetration Testing with OWASP ZAP has been specially designed to help learners gain a good command of Penetration Testing with OWASP ZAP, providing them with a solid foundation of knowledge to become a qualified professional.</p><p>Through this Penetration Testing with OWASP ZAP, you will gain both practical and theoretical understanding of Penetration Testing with OWASP ZAP that will increase your employability in this field, help you stand out from the competition and boost your earning potential in no time.</p><p>Not only that, but this training includes up-to-date knowledge and techniques that will ensure you have the most in-demand skills to rise to the top of the industry. This qualification is fully accredited, broken down into several manageable modules, ideal for aspiring professionals. </p></div>
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										<span>You will be able to incorporate various techniques successfully and understand your customers better.</span>
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                                <h2>Course Curriculum</h2>
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					<td>Things to know about OWASP ZAP</td><td><span>🕐 00:24:00</span></td>
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					<td colspan="4"><strong>Unit02: Configuration Of ZAP</strong></td>
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					<td>OWASP ZAP Course Guide</td><td><span>🕐 00:30:00</span></td>
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Skill Up

Penetration Testing

Online Course Marketing

Online Course Creation

Assessment Practising Certificate (APC)

ACP (Agile Certified Practitioner)

Gain the skills and credentials to kickstart a successful career and learn from the experts with this step-by-step

Penetration Testing with OWASP ZAP

<p>Data Analytics and Business Intelligence course teaches you everything on the topic thoroughly from scratch so you can achieve a certificate for free to showcase your achievement in professional life.</p><p>This Data Analytics and Business Intelligence course is a comprehensive course designed to provide a detailed understanding of the nature of the related sector and your key roles within it.</p><p>The training materials of this Data Analytics and Business Intelligence course are available online for you to learn at your own pace and fast-track your career with ease.</p><p>Data Analytics and Business Intelligence Combo Training Included:</p><ul><li><strong>Course 01: </strong>Data Analytics</li><li><strong>Course 02: </strong>Business Intelligence Analyst</li></ul><p><strong>Key Features </strong></p><ul><li>CPD Accredited Data Analytics and Business Intelligence courses</li><li>Instant 2 PDF certificate</li><li>Fully online, interactive Data Analytics and Business Intelligence course with audio voiceover</li><li>Self-paced learning and laptop, tablet, smartphone-friendly</li><li>24/7 Learning Assistance</li><li>Discounts on bulk purchases</li></ul><p><strong>Enrol now in this </strong><strong>Data Analytics and Business Intelligence</strong><strong> course to excel! </strong></p><p>To become successful in your profession, you must have a specific set of skills to succeed in today's competitive world. In this in-depth Data Analytics and Business Intelligence training course, you will develop the most in-demand skills to kickstart your career, as well as upgrade your existing knowledge &amp; skills.</p><p>The curriculum of the Data Analytics and Business Intelligence course has been designed by experts with years of experience behind them which is extremely dynamic and well-paced to help you understand the subject matter with ease.</p><p><strong>Curriculum</strong></p><p><strong>Course 01: Data Analytics</strong></p><ul><li>Module 01: Introduction to the World of Data</li><li>Module 02: Basics of Data Analytics</li><li>Module 03: Statistics for Data Analytics</li><li>Module 04: Actions Taken in the Data Analysis Process</li><li>Module 05: Gathering the Right Information</li><li>Module 06: Storing Data</li><li>Module 07: Data Mining</li><li>Module 08: Excel for Data Analytics</li><li>Module 09: Tools for Data Analytics</li><li>Module 10: Data-Analytic Thinking</li><li>Module 11: Data Visualisation That Clearly Describes Insights</li><li>Module 12: Data Visualisation Tools</li></ul><p><strong>Course 02: Business Intelligence Analyst</strong></p><ul><li>Module 01: An Introduction to Business Intelligence</li><li>Module 02: Real-time Business Intelligence</li><li>Module 03: Fundamentals of Statistics and Data Science</li><li>Module 04: Fundamentals of SQL</li><li>Module 05: Database Management Essentials</li><li>Module 06: Data Warehouse Concepts</li><li>Module 07: Data Visualisation in Business Intelligence</li><li>Module 08: Basics of Python</li></ul><p><strong>Accreditation</strong></p><p>All of our courses are fully accredited, including this Data Analytics and Business Intelligence course, providing you with up-to-date skills and knowledge and helping you to become more competent and effective in your chosen field.</p><p><strong>Certification</strong></p><p>Once you've successfully completed your Data Analytics and Business Intelligence course, you will immediately be sent a digital certificate. Also, you can have your printed certificate delivered by post (shipping cost £3.99).</p><h2>
        
        <div>CPD</div>
    </h2>

                        <div id="cpd">
                            <div>
                                <div>
                                    <div>
                                        20 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 course is ideal for all employees or anyone who genuinely wishes to learn more about Data Analytics and Business Intelligence basics.</p>
                        </div><h2>
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                            <p>No prior degree or experience is required to enrol in this course.</p>
                        </div><h2>
        
        <div>Certificates</div>
    </h2>

                        <div id="optional_extras">
                                    <h4>Certificate of completion</h4>
        <p>
            Digital certificate -
            Included
        </p>
        <h4>Hard copy certificate</h4>
        <p>
            Hard copy certificate -
            Included
        </p>
            <div> <p>You will get the hard copy certificates for Free! The delivery charge of the hard copy certificate inside the UK is £3.99 each.</p> </div>

                        </div>

Training Express

Data Analytics and Business Intelligence Course

<strong>Learn complete hands-on Regression analysis for practical Statistical modelling and Machine Learning in R</strong>
        <p>With so many R Statistics and Machine Learning courses around, why enroll for this?

Regression analysis is one of the central aspects of both Statistics and Machine Learning based analysis. This course will teach you Regression analysis for both Statistical data analysis and ML in R. It explores relevant concepts in a practical way, from basic to expert level. This course can help you achieve better grades, gain new analysis tools for your academic career, implement your knowledge in a work setting, and make business forecasting-related decisions. You will go all the way from implementing and inferring simple OLS (Ordinary Least Square) regression models to dealing with issues of multicollinearity in regression to ML based regression models.

Become a Regression analysis expert and harness the power of R for your analysis

&bull; Get started with R and RStudio. Install these on your system, learn to load packages, and read in different types of data in R
&bull; Carry out data cleaning and data visualization using R
&bull; Implement Ordinary Least Square (OLS) regression in R and learn how to interpret the results.
&bull; Learn how to deal with multicollinearity both through the variable selection and regularization techniques such as ridge regression
&bull; Carry out variable and regression model selection using both statistical and machine learning techniques, including using cross-validation methods.
&bull; Evaluate the regression model accuracy
&bull; Implement Generalized Linear Models (GLMs) such as logistic regression and Poisson regression. Use logistic regression as a binary classifier to distinguish between male and female voices.
&bull; Use non-parametric techniques such as Generalized Additive Models (GAMs) to work with non-linear and non-parametric data.
&bull; Work with tree-based ML models

All the code and supporting files for this course are available at - https://github.com/PacktPublishing/Regression-Analysis-for-Statistics-and-Machine-Learning-in-R</p>
        <h2>What You Will Learn</h2><p>Implement and infer Ordinary Least Square (OLS) regression using R<br>Apply statistical and ML based regression models to deal with problems such as multicollinearity<br>Carry out the variable selection and assess model accuracy using techniques such as cross-validation<br>Implement and infer Generalized Linear Models (GLMs), including using logistic regression as a binary classifier</p>
        <h2>Audience</h2><p>This course is for students interested in getting started with data science applications in the RStudio environment. Students wishing to learn to implement statistical modeling techniques for regression analysis on real data. Anyone with prior exposure to R who wants to get started with practical data science.</p>
        <h2>Approach</h2><p>This is a practical, hands-on course. We will spend some time dealing with some theoretical concepts related to both statistical and machine learning regression analysis. However, the majority of the course will focus on implementing different techniques on real data and interpreting the results. After each video, you will learn a new concept or technique which you can apply to your own projects.</p>
        <h2>Key Features</h2><p>Provided practical indepth training for you to get started with R * Perform some of the most common advanced regression analysis-based techniques * Use R to perform different statistical and machine learning data analysis and visualization tasks</p>
        <h2>Github Repo</h2><p>https://github.com/packtpublishing/regression-analysis-for-statistics-and-machine-learning-in-r</p>
        <h2>About the Author</h2><h3>Minerva Singh</h3><p>Minerva Singh is a PhD graduate from Cambridge University where she specialized in Tropical Ecology. She is also a part-time Data Scientist. As part of her research, she must carry out extensive data analysis, including spatial data analysis. For this purpose, she prefers to use a combination of freeware tools: R, QGIS, and Python. She does most of her spatial data analysis work using R and QGIS. Apart from being free, these are very powerful tools for data visualization, processing, and analysis. She also holds an MPhil degree in Geography and Environment from Oxford University. She has honed her statistical and data analysis skills through several MOOCs, including The Analytics Edge and Statistical. In addition to spatial data analysis, she is also proficient in statistical analysis, machine learning, and data mining.</p>
        <h2>Course Outline</h2><h4>1. Get Started with Practical Regression Analysis in R</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. INTRODUCTION TO THE COURSE: The Key Concepts and Software Tools</p><p style='margin: 0'>Get Started with Practical Regression Analysis in R: INTRODUCTION TO THE COURSE: The Key Concepts and Software Tools</p></td></tr><tr><td style='padding: 15px;'><p>2. Difference Between Statistical Analysis & Machine Learning</p><p style='margin: 0'>Get Started with Practical Regression Analysis in R: Difference Between Statistical Analysis &amp; Machine Learning</p></td></tr><tr><td style='padding: 15px;'><p>3. Getting Started with R and R Studio</p><p style='margin: 0'>Get Started with Practical Regression Analysis in R: Getting Started with R and R Studio</p></td></tr><tr><td style='padding: 15px;'><p>4. Reading in Data with R</p><p style='margin: 0'>Get Started with Practical Regression Analysis in R: Reading in Data with R</p></td></tr><tr><td style='padding: 15px;'><p>5. Data Cleaning with R</p><p style='margin: 0'>Get Started with Practical Regression Analysis in R: Data Cleaning with R</p></td></tr><tr><td style='padding: 15px;'><p>6. Some More Data Cleaning with R</p><p style='margin: 0'>Get Started with Practical Regression Analysis in R: Some More Data Cleaning with R</p></td></tr><tr><td style='padding: 15px;'><p>7. Basic Exploratory Data Analysis in R</p><p style='margin: 0'>Get Started with Practical Regression Analysis in R: Basic Exploratory Data Analysis in R</p></td></tr><tr><td style='padding: 15px;'><p>8. Conclusion to Section 1</p><p style='margin: 0'>Get Started with Practical Regression Analysis in R: Conclusion to Section 1</p></td></tr></tbody></table><br><h4>2. Ordinary Least Square Regression Modelling</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. OLS Regression- Theory</p><p style='margin: 0'>Ordinary Least Square Regression Modelling: OLS Regression- Theory</p></td></tr><tr><td style='padding: 15px;'><p>2. OLS-Implementation</p><p style='margin: 0'>Ordinary Least Square Regression Modelling: OLS-Implementation</p></td></tr><tr><td style='padding: 15px;'><p>3. More on Result Interpretations</p><p style='margin: 0'>Ordinary Least Square Regression Modelling: More on Result Interpretations</p></td></tr><tr><td style='padding: 15px;'><p>4. Confidence Interval-Theory</p><p style='margin: 0'>Ordinary Least Square Regression Modelling: Confidence Interval-Theory</p></td></tr><tr><td style='padding: 15px;'><p>5. Calculate the Confidence Interval in R</p><p style='margin: 0'>Ordinary Least Square Regression Modelling: Calculate the Confidence Interval in R</p></td></tr><tr><td style='padding: 15px;'><p>6. Confidence Interval and OLS Regressions</p><p style='margin: 0'>Ordinary Least Square Regression Modelling: Confidence Interval and OLS Regressions</p></td></tr><tr><td style='padding: 15px;'><p>7. Linear Regression without Intercept</p><p style='margin: 0'>Ordinary Least Square Regression Modelling: Linear Regression without Intercept</p></td></tr><tr><td style='padding: 15px;'><p>8. Implement ANOVA on OLS Regression</p><p style='margin: 0'>Ordinary Least Square Regression Modelling: Implement ANOVA on OLS Regression</p></td></tr><tr><td style='padding: 15px;'><p>9. Multiple Linear Regression</p><p style='margin: 0'>Ordinary Least Square Regression Modelling: Multiple Linear Regression</p></td></tr><tr><td style='padding: 15px;'><p>10. Multiple Linear regression with Interaction and Dummy Variables</p><p style='margin: 0'>Ordinary Least Square Regression Modelling: Multiple Linear regression with Interaction and Dummy Variables</p></td></tr><tr><td style='padding: 15px;'><p>11. Some Basic Conditions that OLS Models Have to Fulfill</p><p style='margin: 0'>Ordinary Least Square Regression Modelling: Some Basic Conditions that OLS Models Have to Fulfill</p></td></tr><tr><td style='padding: 15px;'><p>12. Conclusions to Section 2</p><p style='margin: 0'>Ordinary Least Square Regression Modelling: Conclusions to Section 2</p></td></tr></tbody></table><br><h4>3. Deal with Multicollinearity in OLS Regression Models</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Identify Multicollinearity</p><p style='margin: 0'>Deal with Multicollinearity in OLS Regression Models: Identify Multicollinearity</p></td></tr><tr><td style='padding: 15px;'><p>2. Doing Regression Analyses with Correlated Predictor Variables</p><p style='margin: 0'>Deal with Multicollinearity in OLS Regression Models: Doing Regression Analyses with Correlated Predictor Variables</p></td></tr><tr><td style='padding: 15px;'><p>3. Principal Component Regression in R</p><p style='margin: 0'>Deal with Multicollinearity in OLS Regression Models: Principal Component Regression in R</p></td></tr><tr><td style='padding: 15px;'><p>4. Partial Least Square Regression in R</p><p style='margin: 0'>Deal with Multicollinearity in OLS Regression Models: Partial Least Square Regression in R</p></td></tr><tr><td style='padding: 15px;'><p>5. Ridge Regression in R</p><p style='margin: 0'>Deal with Multicollinearity in OLS Regression Models: Ridge Regression in R</p></td></tr><tr><td style='padding: 15px;'><p>6. LASSO Regression</p><p style='margin: 0'>Deal with Multicollinearity in OLS Regression Models: LASSO Regression</p></td></tr><tr><td style='padding: 15px;'><p>7. Conclusion to Section 3</p><p style='margin: 0'>Deal with Multicollinearity in OLS Regression Models: Conclusion to Section 3</p></td></tr></tbody></table><br><h4>4. Variable & Model Selection</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Why Do Any Kind of Selection?</p><p style='margin: 0'>Variable &amp; Model Selection: Why Do Any Kind of Selection?</p></td></tr><tr><td style='padding: 15px;'><p>2. Select the Most Suitable OLS Regression Model</p><p style='margin: 0'>Variable &amp; Model Selection: Select the Most Suitable OLS Regression Model</p></td></tr><tr><td style='padding: 15px;'><p>3. Select Model Subsets</p><p style='margin: 0'>Variable &amp; Model Selection: Select Model Subsets</p></td></tr><tr><td style='padding: 15px;'><p>4. Machine Learning Perspective on Evaluate Regression Model Accuracy</p><p style='margin: 0'>Variable &amp; Model Selection: Machine Learning Perspective on Evaluate Regression Model Accuracy</p></td></tr><tr><td style='padding: 15px;'><p>5. Evaluate Regression Model Performance</p><p style='margin: 0'>Variable &amp; Model Selection: Evaluate Regression Model Performance</p></td></tr><tr><td style='padding: 15px;'><p>6. LASSO Regression for Variable Selection</p><p style='margin: 0'>Variable &amp; Model Selection: LASSO Regression for Variable Selection</p></td></tr><tr><td style='padding: 15px;'><p>7. Identify the Contribution of Predictors in Explaining the Variation in Y</p><p style='margin: 0'>Variable &amp; Model Selection: Identify the Contribution of Predictors in Explaining the Variation in Y</p></td></tr><tr><td style='padding: 15px;'><p>8. Conclusions to Section 4</p><p style='margin: 0'>Variable &amp; Model Selection: Conclusions to Section 4</p></td></tr></tbody></table><br><h4>5. Dealing with Other Violations of the OLS Regression Models</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Data Transformations</p><p style='margin: 0'>Dealing with Other Violations of the OLS Regression Models: Data Transformations</p></td></tr><tr><td style='padding: 15px;'><p>2. Robust Regression-Deal with Outliers</p><p style='margin: 0'>Dealing with Other Violations of the OLS Regression Models: Robust Regression-Deal with Outliers</p></td></tr><tr><td style='padding: 15px;'><p>3. Dealing with Heteroscedasticity</p><p style='margin: 0'>Dealing with Other Violations of the OLS Regression Models: Dealing with Heteroscedasticity</p></td></tr><tr><td style='padding: 15px;'><p>4. Conclusions to Section 5</p><p style='margin: 0'>Dealing with Other Violations of the OLS Regression Models: Conclusions to Section 5</p></td></tr></tbody></table><br><h4>6. Generalized Linear Models (GLMs)</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. What are GLMs?</p><p style='margin: 0'>Generalized Linear Models (GLMs): What are GLMs?</p></td></tr><tr><td style='padding: 15px;'><p>2. Logistic regression</p><p style='margin: 0'>Generalized Linear Models (GLMs): Logistic regression</p></td></tr><tr><td style='padding: 15px;'><p>3. Logistic Regression for Binary Response Variable</p><p style='margin: 0'>Generalized Linear Models (GLMs): Logistic Regression for Binary Response Variable</p></td></tr><tr><td style='padding: 15px;'><p>4. Multinomial Logistic Regression</p><p style='margin: 0'>Generalized Linear Models (GLMs): Multinomial Logistic Regression</p></td></tr><tr><td style='padding: 15px;'><p>5. Regression for Count Data</p><p style='margin: 0'>Generalized Linear Models (GLMs): Regression for Count Data</p></td></tr><tr><td style='padding: 15px;'><p>6. Goodness of fit testing</p><p style='margin: 0'>Generalized Linear Models (GLMs): Goodness of fit testing</p></td></tr><tr><td style='padding: 15px;'><p>7. Conclusions to Section 6</p><p style='margin: 0'>Generalized Linear Models (GLMs): Conclusions to Section 6</p></td></tr></tbody></table><br><h4>7. Working with Non-Parametric and Non-Linear Data</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Polynomial and Non-linear regression</p><p style='margin: 0'>Working with Non-Parametric and Non-Linear Data: Polynomial and Non-linear regression</p></td></tr><tr><td style='padding: 15px;'><p>2. Generalized Additive Models (GAMs) in R</p><p style='margin: 0'>Working with Non-Parametric and Non-Linear Data: Generalized Additive Models (GAMs) in R</p></td></tr><tr><td style='padding: 15px;'><p>3. Boosted GAM Regression</p><p style='margin: 0'>Working with Non-Parametric and Non-Linear Data: Boosted GAM Regression</p></td></tr><tr><td style='padding: 15px;'><p>4. Multivariate Adaptive Regression Splines (MARS)</p><p style='margin: 0'>Working with Non-Parametric and Non-Linear Data: Multivariate Adaptive Regression Splines (MARS)</p></td></tr><tr><td style='padding: 15px;'><p>5. CART-Regression Trees in R</p><p style='margin: 0'>Working with Non-Parametric and Non-Linear Data: CART-Regression Trees in R</p></td></tr><tr><td style='padding: 15px;'><p>6. Conditional Inference Trees</p><p style='margin: 0'>Working with Non-Parametric and Non-Linear Data: Conditional Inference Trees</p></td></tr><tr><td style='padding: 15px;'><p>7. Random Forest(RF)</p><p style='margin: 0'>Working with Non-Parametric and Non-Linear Data: Random Forest(RF)</p></td></tr><tr><td style='padding: 15px;'><p>8. Gradient Boosting Regression</p><p style='margin: 0'>Working with Non-Parametric and Non-Linear Data: Gradient Boosting Regression</p></td></tr><tr><td style='padding: 15px;'><p>9. ML Model Selection</p><p style='margin: 0'>Working with Non-Parametric and Non-Linear Data: ML Model Selection</p></td></tr><tr><td style='padding: 15px;'><p>10. Conclusions to Section 7</p><p style='margin: 0'>Working with Non-Parametric and Non-Linear Data: Conclusions to Section 7</p></td></tr></tbody></table>

Statistics

Learn complete hands-on Regression analysis for practical Statistical modelling and Machine Learning in R

Regression Analysis for Statistics & Machine Learning in R

<div id="course-pills-1">Duration<p>4 Days</p><p>24 CPD hours</p>This course is intended for<p></p><p>This course is designed for data scientists with existing knowledge of Python and machine learning frameworks like Scikit-Learn, PyTorch, and Tensorflow, who want to build and operate machine learning solutions in the cloud.</p><p></p>Overview<p>Learn how to operate machine learning solutions at cloud scale using Azure Machine Learning. This course teaches you to leverage your existing knowledge of Python and machine learning to manage data ingestion and preparation, model training and deployment, and machine learning solution monitoring in Microsoft Azure.</p><p></p><p>Learn how to operate machine learning solutions at cloud scale using Azure Machine Learning. This course teaches you to leverage your existing knowledge of Python and machine learning to manage data ingestion and preparation, model training and deployment, and machine learning solution monitoring with Azure Machine Learning and MLflow.</p><p></p>Prerequisites<p></p><li>Creating cloud resources in Microsoft Azure.</li>  <li>Using Python to explore and visualize data.</li>  <li>Training and validating machine learning models using common frameworks like Scikit-Learn, PyTorch, and TensorFlow.</li>  <li>Working with containers</li>  <li>AI-900T00: Microsoft Azure AI Fundamentals is recommended, or the equivalent experience.</li><p></p></div><div id="course-pills-2"><h3>1 - Design a data ingestion strategy for machine learning projects</h3> <ul> <li>Identify your data source and format</li> <li>Choose how to serve data to machine learning workflows</li> <li>Design a data ingestion solution</li> </ul> <h3>2 - Design a machine learning model training solution</h3> <ul> <li>Identify machine learning tasks</li> <li>Choose a service to train a machine learning model</li> <li>Decide between compute options</li> </ul> <h3>3 - Design a model deployment solution</h3> <ul> <li>Understand how model will be consumed</li> <li>Decide on real-time or batch deployment</li> </ul> <h3>4 - Design a machine learning operations solution</h3> <ul> <li>Explore an MLOps architecture</li> <li>Design for monitoring</li> <li>Design for retraining</li> </ul> <h3>5 - Explore Azure Machine Learning workspace resources and assets</h3> <ul> <li>Create an Azure Machine Learning workspace</li> <li>Identify Azure Machine Learning resources</li> <li>Identify Azure Machine Learning assets</li> <li>Train models in the workspace</li> </ul> <h3>6 - Explore developer tools for workspace interaction</h3> <ul> <li>Explore the studio</li> <li>Explore the Python SDK</li> <li>Explore the CLI</li> </ul> <h3>7 - Make data available in Azure Machine Learning</h3> <ul> <li>Understand URIs</li> <li>Create a datastore</li> <li>Create a data asset</li> </ul> <h3>8 - Work with compute targets in Azure Machine Learning</h3> <ul> <li>Choose the appropriate compute target</li> <li>Create and use a compute instance</li> <li>Create and use a compute cluster</li> </ul> <h3>9 - Work with environments in Azure Machine Learning</h3> <ul> <li>Understand environments</li> <li>Explore and use curated environments</li> <li>Create and use custom environments</li> </ul> <h3>10 - Find the best classification model with Automated Machine Learning</h3> <ul> <li>Preprocess data and configure featurization</li> <li>Run an Automated Machine Learning experiment</li> <li>Evaluate and compare models</li> </ul> <h3>11 - Track model training in Jupyter notebooks with MLflow</h3> <ul> <li>Configure MLflow for model tracking in notebooks</li> <li>Train and track models in notebooks</li> </ul> <h3>12 - Run a training script as a command job in Azure Machine Learning</h3> <ul> <li>Convert a notebook to a script</li> <li>Run a script as a command job</li> <li>Use parameters in a command job</li> </ul> <h3>13 - Track model training with MLflow in jobs</h3> <ul> <li>Track metrics with MLflow</li> <li>View metrics and evaluate models</li> </ul> <h3>14 - Perform hyperparameter tuning with Azure Machine Learning</h3> <ul> <li>Define a search space</li> <li>Configure a sampling method</li> <li>Configure early termination</li> <li>Use a sweep job for hyperparameter tuning</li> </ul> <h3>15 - Run pipelines in Azure Machine Learning</h3> <ul> <li>Create components</li> <li>Create a pipeline</li> <li>Run a pipeline job</li> </ul> <h3>16 - Register an MLflow model in Azure Machine Learning</h3> <ul> <li>Log models with MLflow</li> <li>Understand the MLflow model format</li> <li>Register an MLflow model</li> </ul> <h3>17 - Create and explore the Responsible AI dashboard for a model in Azure Machine Learning</h3> <ul> <li>Understand Responsible AI</li> <li>Create the Responsible AI dashboard</li> <li>Evaluate the Responsible AI dashboard</li> </ul> <h3>18 - Deploy a model to a managed online endpoint</h3> <ul> <li>Explore managed online endpoints</li> <li>Deploy your MLflow model to a managed online endpoint</li> <li>Deploy a model to a managed online endpoint</li> <li>Test managed online endpoints</li> </ul> <h3>19 - Deploy a model to a batch endpoint</h3> <ul> <li>Understand and create batch endpoints</li> <li>Deploy your MLflow model to a batch endpoint</li> <li>Deploy a custom model to a batch endpoint</li> <li>Invoke and troubleshoot batch endpoints</li> </ul></div>

Nexus Human

Data Engineering

Microsoft AZ-900

Microsoft Azure

Microsoft AZ-303

Microsoft AZ-700

Azure Machine Learning

DP-100T01 Designing and Implementing a Data Science Solution on Azure

"Start your career as a Certified Python Programmer and earn up to £70,000 per Year."
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 CPD 
100 CPD hours / points  Accredited by CPD Quality Standards
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 Requirements 
No experience required. Just enrol & start learning python.
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 Certificates 
CPD Accredited e-Certificate
 Digital certificate - Included 
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 Hard copy certificate - Included 
Enrolment Letter
 Digital certificate - Included 
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 Hard copy certificate - Included 
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Academy for Health and Fitness

Programming Fundamentals

Career Development

IT Certifications

Become an IT professional with our Python Certification - IT Job Ready Program! Gain comprehensive skills in Python programming, data analysis, and automation. We offer a money-back guarantee if you don't secure a job within six months of completion. Enroll now and jumpstart your tech career!


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Python Certification - IT Job Ready Program with Money Back Guarantee

<strong>Learn Python Programming the Easy Way, Complete with Examples, Quizzes, Exercises and more. Learn Python 2 and Python 3.</strong>
        <p>This course will teach you Python in a practical manner, complete with examples, quizzes, exercises, and more. You will learn when to use Python 2 and Python 3; both versions are covered in the course and you will learn to program in both. You'll learn how to take tedious and repetitious tasks and turn them into programs that will save you time and simplify your life on Linux, UNIX, or MAC systems. You will learn how to prepare your computer for programming in Python; how to work with various data types including strings, lists, tuples, dictionaries, Booleans; how to perform mathematical operations using Python, and more.</p>
        <h2>What You Will Learn</h2><p>When to use Python 2 and when to use Python 3.<br>How to install Python on Windows, Mac, and Linux.<br>How to prepare your computer for programming in Python.<br>The various ways to run a Python program on Windows, Mac, and Linux.<br>Suggested text editors and Integrated Development Environments to use when coding in Python.<br>How to work with various data types including strings, lists, tuples, dictionaries, Booleans, and more.<br>What variables are and when to use them.<br>How to perform mathematical operations using Python.<br>How to capture input from a user.<br>Ways to control the flow of your programs.<br>The importance of white space in Python.<br>How to organize your Python programs: learn what goes where.<br>What modules are, when you should use them, and how to create your own.<br>How to define and use functions.<br>Important built-in Python functions that you ll use often.<br>How to read from and write to files.<br>The difference between binary and text files.<br>Various ways of getting help, including finding Python documentation.<br></p>
        <h2>Audience</h2><p>This course targets anyone interested in Python programming, Python scripting, or computer programming in general; those who want to become a highly paid Python developer; and those who want to open up doors in their IT career by learning one of the world's most popular and in-demand programming languages.</p>
        <h2>Approach</h2><p>A complete course packed with step-by-step instructions, practice exercises with solutions, and quizzes. This course is clearly divided into small parts to help you understand each part individually and learn at your own pace. Once you've completed this course you'll know how to write programs that will run on the Linux, Mac, and Windows operating systems. You can even take what you've learned and apply it to web applications. </p>
        <h2>Key Features</h2><p>How to install Python on Windows, Mac, and Linux. * A practical tutorial designed for Python beginners. * </p>
        <h2>Github Repo</h2><p>https://github.com/packtpublishing/python-for-beginners-learn-python-programming-python-3-</p>
        <h2>About the Author</h2><h3>Jason Cannon</h3><p>Jason Cannon is a professional system administrator, consultant, and author. He started his career as a Unix and Linux System engineer in 1999. Since that time, he has utilized his Linux skills at companies such as Xerox, UPS, Hewlett-Packard, and Amazon.com. Additionally, he has acted as a technical consultant and independent contractor for small businesses and Fortune 500 companies.

Jason has professional experience with CentOS, RedHat Enterprise Linux, SUSE Linux Enterprise Server, and Ubuntu. He has used several Linux distributions on personal projects including Debian, Slackware, CrunchBang, and others. In addition to Linux, Jason has experience supporting proprietary Unix operating systems including AIX, HP-UX, and Solaris. He enjoys teaching others how to use and exploit the power of the Linux operating system.</p>
        <h2>Course Outline</h2><h4>1. Course Overview and Downloads</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Course Overview</p><p style='margin: 0'>Course Overview and Downloads: Course Overview</p></td></tr></tbody></table><br><h4>2. Python Setup</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Python 2 vs Python 3</p><p style='margin: 0'>Python Setup: Python 2 vs Python 3</p></td></tr><tr><td style='padding: 15px;'><p>2. Installing Python on Windows</p><p style='margin: 0'>Python Setup: Installing Python on Windows</p></td></tr><tr><td style='padding: 15px;'><p>3. Installing Python on Mac</p><p style='margin: 0'>Python Setup: Installing Python on Mac</p></td></tr><tr><td style='padding: 15px;'><p>4. Installing Python on Linux</p><p style='margin: 0'>Python Setup: Installing Python on Linux</p></td></tr><tr><td style='padding: 15px;'><p>5. Writing Python Programs</p><p style='margin: 0'>Python Setup: Writing Python Programs</p></td></tr><tr><td style='padding: 15px;'><p>6. Running Python Programs</p><p style='margin: 0'>Python Setup: Running Python Programs</p></td></tr></tbody></table><br><h4>3. Strings and Variables</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Section Overview</p><p style='margin: 0'>Strings and Variables: Section Overview</p></td></tr><tr><td style='padding: 15px;'><p>2. Variables and Strings</p><p style='margin: 0'>Strings and Variables: Variables and Strings</p></td></tr><tr><td style='padding: 15px;'><p>3. Functions and Printing</p><p style='margin: 0'>Strings and Variables: Functions and Printing</p></td></tr><tr><td style='padding: 15px;'><p>4. String Methods</p><p style='margin: 0'>Strings and Variables: String Methods</p></td></tr><tr><td style='padding: 15px;'><p>5. String Concatenation</p><p style='margin: 0'>Strings and Variables: String Concatenation</p></td></tr><tr><td style='padding: 15px;'><p>6. Formatting Strings</p><p style='margin: 0'>Strings and Variables: Formatting Strings</p></td></tr><tr><td style='padding: 15px;'><p>7. Section Summary</p><p style='margin: 0'>Strings and Variables: Section Summary</p></td></tr><tr><td style='padding: 15px;'><p>8. Solutions to the Practice Exercises - #1 - Video</p><p style='margin: 0'>Strings and Variables: Solutions to the Practice Exercises - #1 - Video</p></td></tr><tr><td style='padding: 15px;'><p>9. Solutions to the Practice Exercises - #2 - Video</p><p style='margin: 0'>Strings and Variables: Solutions to the Practice Exercises - #2 - Video</p></td></tr><tr><td style='padding: 15px;'><p>10. Solutions to the Practice Exercises - #3 - Video</p><p style='margin: 0'>Strings and Variables: Solutions to the Practice Exercises - #3 - Video</p></td></tr></tbody></table><br><h4>4. Numbers and Math</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Section Overview</p><p style='margin: 0'>Numbers and Math: Section Overview</p></td></tr><tr><td style='padding: 15px;'><p>2. Numbers, Numeric Operations, and Numeric Functions</p><p style='margin: 0'>Numbers and Math: Numbers, Numeric Operations, and Numeric Functions</p></td></tr><tr><td style='padding: 15px;'><p>3. Comments</p><p style='margin: 0'>Numbers and Math: Comments</p></td></tr><tr><td style='padding: 15px;'><p>4. Section Summary</p><p style='margin: 0'>Numbers and Math: Section Summary</p></td></tr></tbody></table><br><h4>5. Booleans and Conditionals</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Section Overview</p><p style='margin: 0'>Booleans and Conditionals: Section Overview</p></td></tr><tr><td style='padding: 15px;'><p>2. Booleans</p><p style='margin: 0'>Booleans and Conditionals: Booleans</p></td></tr><tr><td style='padding: 15px;'><p>3. Conditionals</p><p style='margin: 0'>Booleans and Conditionals: Conditionals</p></td></tr><tr><td style='padding: 15px;'><p>4. Section Summary</p><p style='margin: 0'>Booleans and Conditionals: Section Summary</p></td></tr></tbody></table><br><h4>6. Functions</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Section Overview</p><p style='margin: 0'>Functions: Section Overview</p></td></tr><tr><td style='padding: 15px;'><p>2. Functions, Part I</p><p style='margin: 0'>Functions: Functions, Part I</p></td></tr><tr><td style='padding: 15px;'><p>3. Functions, Part II</p><p style='margin: 0'>Functions: Functions, Part II</p></td></tr><tr><td style='padding: 15px;'><p>4. Section Summary</p><p style='margin: 0'>Functions: Section Summary</p></td></tr></tbody></table><br><h4>7. Lists</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Section Overview</p><p style='margin: 0'>Lists: Section Overview</p></td></tr><tr><td style='padding: 15px;'><p>2. Lists</p><p style='margin: 0'>Lists: Lists</p></td></tr><tr><td style='padding: 15px;'><p>3. Slices</p><p style='margin: 0'>Lists: Slices</p></td></tr><tr><td style='padding: 15px;'><p>4. Exception Handling</p><p style='margin: 0'>Lists: Exception Handling</p></td></tr><tr><td style='padding: 15px;'><p>5. Loops</p><p style='margin: 0'>Lists: Loops</p></td></tr><tr><td style='padding: 15px;'><p>6. Sorting and Ranges</p><p style='margin: 0'>Lists: Sorting and Ranges</p></td></tr><tr><td style='padding: 15px;'><p>7. Section Summary</p><p style='margin: 0'>Lists: Section Summary</p></td></tr></tbody></table><br><h4>8. Dictionaries</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Section Overview</p><p style='margin: 0'>Dictionaries: Section Overview</p></td></tr><tr><td style='padding: 15px;'><p>2. Dictionaries - Part I</p><p style='margin: 0'>Dictionaries: Dictionaries - Part I</p></td></tr><tr><td style='padding: 15px;'><p>3. Dictionaries - Part II</p><p style='margin: 0'>Dictionaries: Dictionaries - Part II</p></td></tr><tr><td style='padding: 15px;'><p>4. Section Summary</p><p style='margin: 0'>Dictionaries: Section Summary</p></td></tr></tbody></table><br><h4>9. Tuples</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Section Overview</p><p style='margin: 0'>Tuples: Section Overview</p></td></tr><tr><td style='padding: 15px;'><p>2. Tuples</p><p style='margin: 0'>Tuples: Tuples</p></td></tr><tr><td style='padding: 15px;'><p>3. Section Summary</p><p style='margin: 0'>Tuples: Section Summary</p></td></tr></tbody></table><br><h4>10. Files</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Section Overview</p><p style='margin: 0'>Files: Section Overview</p></td></tr><tr><td style='padding: 15px;'><p>2. Files, Part I</p><p style='margin: 0'>Files: Files, Part I</p></td></tr><tr><td style='padding: 15px;'><p>3. Files, Part II</p><p style='margin: 0'>Files: Files, Part II</p></td></tr><tr><td style='padding: 15px;'><p>4. Section Summary</p><p style='margin: 0'>Files: Section Summary</p></td></tr></tbody></table><br><h4>11. Modules</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Section Overview</p><p style='margin: 0'>Modules: Section Overview</p></td></tr><tr><td style='padding: 15px;'><p>2. Modules, Part I</p><p style='margin: 0'>Modules: Modules, Part I</p></td></tr><tr><td style='padding: 15px;'><p>3. Modules, Part II</p><p style='margin: 0'>Modules: Modules, Part II</p></td></tr><tr><td style='padding: 15px;'><p>4. Section Overview</p><p style='margin: 0'>Modules: Section Overview</p></td></tr></tbody></table>

Python

Learn Python Programming the Easy Way, Complete with Examples, Quizzes, Exercises and more. Learn Python 2 and Python 3.

Python for Beginners: Learn Python Programming (Python 3)

<p><strong>Start your career in Data Science and earn up to £90,000 per month.</strong></p><p>Are you eager to dive into the high-speed world of Data Science powered by Python? In the UK alone, Data Scientist job postings witnessed a dramatic increase of 67% in 2022, emphasising the burgeoning demand for proficient Python programmers. Amid such a dynamic job market, our online course - Data Science with Python, serves as your stepping-stone to a universe of opportunities. Whether you're taking your first step into the realm of Data Science or aiming to augment your existing skills, our program offers peerless support, ensuring you're industry-ready by the time you complete our course.</p><p><strong>Our mission is simple</strong> - to be your trusted partner every step of the way, from training to employment.</p><p>In addition to teaching you the technical skills you need, we will also provide you with <strong>career mentoring and support</strong>. We will help you build your resume, prepare for interviews, and land your <strong>dream job</strong>. We also have<strong> partnerships with many companies</strong> that are hiring Data <strong>Scientists</strong>, so we can help you get your foot in the door.</p><p>If you are not happy with our service, we also offer a <strong>100% money-back guarantee</strong>. So what are you waiting for? Enrol in our Data Scientist with Python Training Program today and start your journey to becoming a successful Data Scientist!</p><p>If you have any questions, you can <strong>contact us</strong>. We will be happy to provide you with all the information you need.</p><p><strong>Why Choose Us?</strong></p><p>So, what sets us apart from other programs? Let's dive into the exceptional benefits you'll experience when you join our Data Scientist with Python:</p><ul><li><strong>Personalised Guidance:</strong> We believe in the power of individual attention. Our experienced mentors will provide one-on-one counselling sessions tailored to your specific needs. Whether you're a beginner or have some Python experience, we will guide you towards honing your skills and developing a strong foundation in both Data Science and Python.<br /><br /></li><li><strong>One-On-One Consultation Sessions with Industry Experts:</strong> Gain invaluable insights and guidance from seasoned professionals who have thrived in the Data Science field. Our consultation sessions provide you with insider tips, tricks, and advice, empowering you to navigate the industry with confidence and expertise.<br /><br /></li><li><strong>Extensive Job Opportunities:</strong> We have established partnerships with numerous companies actively seeking Data Scientists. Through our network, we'll connect you with exclusive job openings that are not easily accessible elsewhere.<br /><br /></li><li><strong>Interview Preparation:</strong> No more stress over unexpected interview questions. We provide you with access to a comprehensive database of potential interview questions curated over years of industry experience. Walk into your interviews confident, well-prepared, and ready to impress.<br /><br /></li><li><strong>Money-Back Guarantee:</strong> Your satisfaction is our top priority. We are confident in the quality of our training and support, which is why we offer a <strong>100% money-back guarantee. </strong>If, for any reason, you're not happy with our services, we'll refund your investment, no questions asked. We believe in the value we provide and want you to feel completely satisfied with your decision to join us.<br /><br /></li><li><strong>Continuous Career Support: </strong>Our commitment doesn't end when you secure a job. We'll be there for you throughout your career journey, offering continued support and guidance.</li></ul><p><strong>Here are the courses we will provide once you enrol in the program:</strong></p><ul><li>Course 01: Business and Data Analytics for Beginners</li><li>Course 02: Quick Data Science Approach from Scratch</li><li>Course 03: Learn MySQL from Scratch for Data Science and Analytics</li><li>Course 04: SQL for Data Science, Data Analytics and Data Visualization</li><li>Course 05: Statistics &amp; Probability for Data Science &amp; Machine Learning</li><li>Course 06: R Programming for Data Science</li><li>Course 07: Python Data Science with Numpy, Pandas and Matplotlib</li><li>Course 08: Complete Python Machine Learning &amp; Data Science Fundamentals</li><li>Course 09: 2021 Data Science &amp; Machine Learning with R from A-Z</li><li>Course 10: Python Programming from Scratch with My SQL Database</li><li>Course 11: Level 2 Python Course</li><li>Course 12: Machine Learning for Predictive Maps in Python and Leaflet</li><li>Course 13: Python Programming Bible | Networking, GUI, Email, XML, CGI</li><li>Course 14: Python for Spatial Analysis in ArcGIS</li><li>Course 15: Ultimate Python Training for Beginners</li><li>Course 16: PyScript Fundamentals Training</li></ul><p><strong>How Can We Offer Job Guarantees?</strong></p><p>HF Online provides consultancy, professional and educational services to many of the companies in the UK. During our intense exclusive training program, you will not just gain and complete the industry valuable certification but will gain industry experience as well, which is imperative to get your 1st job in the sector.</p> <p><strong>The </strong><strong>Data Scientist with Python </strong><strong>Program is completed in 9 easy steps:<br /><br /></strong></p><p><strong>Step 1: Enrol in the Programme</strong></p><p>Begin your exciting journey with us by enrolling in the Data Science with Python Training program. Complete your registration and make a secure online payment. Remember, we offer a 14-day money-back guarantee if you're not completely satisfied.</p><p>After you enrol in the Program, you will get lifetime access to 16 premium courses related to Data Science with Python. These courses will teach you the knowledge and skills required to become a successful Data Scientist. Our customer service team will help you and keep in contact with you every step of the way. So you won't have to worry about a thing!</p><p><strong>Step 2: Initial One-On-One Counselling Session</strong></p><p>Once enrolled, you will be paired with a dedicated career mentor. Schedule your first one-on-one session to discuss your career aspirations, skills, experience, and any areas for potential growth. This conversation will shape your learning and development path.<br /><br /></p><p><strong>Step 3 - </strong><strong>Certification upon Course Completion</strong></p><p>After learning from the courses, you must obtain certificates for each course. There will be exams for every course, and you have to pass them to get your certificate. To pass successfully, you must get 90% marks. Once you pass the exams, you will receive hardcopy certificates. These certificates will prove that you're an expert in the subject.<br /><br /></p><p><strong>Step 4: </strong><strong>CV Revamping</strong></p><p>Our team of professionals will build you a compelling CV and <strong>LinkedIn profile</strong>. We'll ensure it presents your skills and qualifications effectively and is tailored to the needs and expectations of the Data Science with Python industry. With these powerful tools in hand, you'll be fully prepared to tackle job interviews confidently. <br /><br /></p><p><strong>Step 5: Building Network and Submitting CV</strong></p><p>We understand the power of casting a wide net. We'll strategically submit your CV to various platforms and networks, expanding your reach and connecting you with valuable opportunities that align with your career goals. We will also make connections with many<strong> high-profile individuals and companies</strong> through your LinkedIn profile.<br /><br /></p><p><strong>Step 6: Interview Preparation</strong></p><p>With your CV ready, we'll move on to interview preparation. Gain exclusive access to our database of potential interview questions. Through simulated interviews with your mentor, you'll practice your responses and receive valuable feedback to further refine your skills.<br /><br /></p><p><strong>Step 7: Securing Job Interviews</strong></p><p>Leveraging our partnerships with leading companies, <strong>we'll secure job interviews for you</strong>. We'll ensure you get the opportunity to showcase your skills to potential employers and <strong>get the dream job you want</strong>.<br /><br /></p><p><strong>Step 8: Post-Interview Support</strong></p><p>Post-interview, we'll provide a debriefing session to reflect on your performance and identify areas of improvement for future interviews if necessary. Remember, our commitment extends until you land your dream job.<br /><br /></p><p><strong>Step 9: Celebrate Your New Job!</strong></p><p>Once you've secured your dream job in Data Science with Python, it's time to celebrate! However, our support doesn't end there. We'll provide you with ongoing career advice to ensure you continue to thrive in your new role.</p><p>We're excited to accompany you on this journey to success. Enrol today, and let's get started! Your path to a successful career in Data Science with Python begins with us.</p> <h2>
        
        <div>CPD</div>
    </h2>

                        <div id="cpd">
                            <div>
                                <div>
                                    <div>
                                        100 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>Beginners with an interest in Data Science and Python programming.</li><li>Programmers and Software Engineers looking to transition into Data Science.</li><li>Business Analysts and Project Managers aiming to leverage Data Science in their domains.</li><li>Researchers and Academics who wish to utilise Python for complex data analysis.</li></ul>
                        </div> <h2>
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                            <p>No experience required. Just enrol &amp; start learning.</p>
                        </div> <h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                            <ul><li>Data Scientist: £60,000 - £90,000</li><li>Machine Learning Engineer: £65,000 - £100,000</li><li>Data Analyst: £40,000 - £60,000</li><li>Business Intelligence Analyst: £45,000 - £70,000</li><li>Data Engineer: £50,000 - £80,000</li><li>Big Data Architect: £70,000 - £120,000</li></ul>
                        </div> <h2>
        
        <div>Certificates</div>
    </h2>

                        <div id="optional_extras">
                                    <h4>CPD Accredited e-Certificate</h4>
        <p>
            Digital certificate -
            Included
        </p>
        <h4>CPD Accredited Framed (Hardcopy) Certificate</h4>
        <p>
            Hard copy certificate -
            Included
        </p>
        <h4>Enrolment Letter</h4>
        <p>
            Digital certificate -
            Included
        </p>
        <h4>QLS Endorsed Hard Copy Certificate</h4>
        <p>
            Hard copy certificate -
            Included
        </p>
        <h4>Student ID Card</h4>
        <p>
            Digital certificate -
            Included
        </p>

                        </div>

Start your career in Data Science and earn up to £90,000 per month.
Are you eager to dive into the high-speed world of Data Science powered by Python? In the UK alone, Data Scientist job postings witnessed a dramatic increase of 67% in 2022, emphasising the burgeoning demand for proficient Python programmers. Amid such a dynamic job market, our online course - Data Science with Python, serves as your stepping-stone to a universe of opportunities. Whether you're taking your first step into the realm of Data Science or aiming to augment your existing skills, our program offers peerless support, ensuring you're industry-ready by the time you complete our course.
Our mission is simple - to be your trusted partner every step of the way, from training to employment.
In addition to teaching you the technical skills you need, we will also provide you with career mentoring and support. We will help you build your resume, prepare for interviews, and land your dream job. We also have partnerships with many companies that are hiring Data Scientists, so we can help you get your foot in the door.
If you are not happy with our service, we also offer a 100% money-back guarantee. So what are you waiting for? Enrol in our Data Scientist with Python Training Program today and start your journey to becoming a successful Data Scientist!
If you have any questions, you can contact us. We will be happy to provide you with all the information you need.
Why Choose Us?
So, what sets us apart from other programs? Let's dive into the exceptional benefits you'll experience when you join our Data Scientist with Python:
Personalised Guidance: We believe in the power of individual attention. Our experienced mentors will provide one-on-one counselling sessions tailored to your specific needs. Whether you're a beginner or have some Python experience, we will guide you towards honing your skills and developing a strong foundation in both Data Science and Python.
One-On-One Consultation Sessions with Industry Experts: Gain invaluable insights and guidance from seasoned professionals who have thrived in the Data Science field. Our consultation sessions provide you with insider tips, tricks, and advice, empowering you to navigate the industry with confidence and expertise.
Extensive Job Opportunities: We have established partnerships with numerous companies actively seeking Data Scientists. Through our network, we'll connect you with exclusive job openings that are not easily accessible elsewhere.
Interview Preparation: No more stress over unexpected interview questions. We provide you with access to a comprehensive database of potential interview questions curated over years of industry experience. Walk into your interviews confident, well-prepared, and ready to impress.
Money-Back Guarantee: Your satisfaction is our top priority. We are confident in the quality of our training and support, which is why we offer a 100% money-back guarantee. If, for any reason, you're not happy with our services, we'll refund your investment, no questions asked. We believe in the value we provide and want you to feel completely satisfied with your decision to join us.
Continuous Career Support: Our commitment doesn't end when you secure a job. We'll be there for you throughout your career journey, offering continued support and guidance.
Here are the courses we will provide once you enrol in the program:
Course 01: Business and Data Analytics for Beginners
Course 02: Quick Data Science Approach from Scratch
Course 03: Learn MySQL from Scratch for Data Science and Analytics
Course 04: SQL for Data Science, Data Analytics and Data Visualization
Course 05: Statistics & Probability for Data Science & Machine Learning
Course 06: R Programming for Data Science
Course 07: Python Data Science with Numpy, Pandas and Matplotlib
Course 08: Complete Python Machine Learning & Data Science Fundamentals
Course 09: 2021 Data Science & Machine Learning with R from A-Z
Course 10: Python Programming from Scratch with My SQL Database
Course 11: Level 2 Python Course
Course 12: Machine Learning for Predictive Maps in Python and Leaflet
Course 13: Python Programming Bible | Networking, GUI, Email, XML, CGI
Course 14: Python for Spatial Analysis in ArcGIS
Course 15: Ultimate Python Training for Beginners
Course 16: PyScript Fundamentals Training
How Can We Offer Job Guarantees?
HF Online provides consultancy, professional and educational services to many of the companies in the UK. During our intense exclusive training program, you will not just gain and complete the industry valuable certification but will gain industry experience as well, which is imperative to get your 1st job in the sector.
The Data Scientist with Python Program is completed in 9 easy steps:


Step 1: Enrol in the Programme
Begin your exciting journey with us by enrolling in the Data Science with Python Training program. Complete your registration and make a secure online payment. Remember, we offer a 14-day money-back guarantee if you're not completely satisfied.
After you enrol in the Program, you will get lifetime access to 16 premium courses related to Data Science with Python. These courses will teach you the knowledge and skills required to become a successful Data Scientist. Our customer service team will help you and keep in contact with you every step of the way. So you won't have to worry about a thing!
Step 2: Initial One-On-One Counselling Session
Once enrolled, you will be paired with a dedicated career mentor. Schedule your first one-on-one session to discuss your career aspirations, skills, experience, and any areas for potential growth. This conversation will shape your learning and development path.


Step 3 - Certification upon Course Completion
After learning from the courses, you must obtain certificates for each course. There will be exams for every course, and you have to pass them to get your certificate. To pass successfully, you must get 90% marks. Once you pass the exams, you will receive hardcopy certificates. These certificates will prove that you're an expert in the subject.


Step 4: CV Revamping
Our team of professionals will build you a compelling CV and LinkedIn profile. We'll ensure it presents your skills and qualifications effectively and is tailored to the needs and expectations of the Data Science with Python industry. With these powerful tools in hand, you'll be fully prepared to tackle job interviews confidently. 


Step 5: Building Network and Submitting CV
We understand the power of casting a wide net. We'll strategically submit your CV to various platforms and networks, expanding your reach and connecting you with valuable opportunities that align with your career goals. We will also make connections with many high-profile individuals and companies through your LinkedIn profile.


Step 6: Interview Preparation
With your CV ready, we'll move on to interview preparation. Gain exclusive access to our database of potential interview questions. Through simulated interviews with your mentor, you'll practice your responses and receive valuable feedback to further refine your skills.


Step 7: Securing Job Interviews
Leveraging our partnerships with leading companies, we'll secure job interviews for you. We'll ensure you get the opportunity to showcase your skills to potential employers and get the dream job you want.


Step 8: Post-Interview Support
Post-interview, we'll provide a debriefing session to reflect on your performance and identify areas of improvement for future interviews if necessary. Remember, our commitment extends until you land your dream job.


Step 9: Celebrate Your New Job!
Once you've secured your dream job in Data Science with Python, it's time to celebrate! However, our support doesn't end there. We'll provide you with ongoing career advice to ensure you continue to thrive in your new role.
We're excited to accompany you on this journey to success. Enrol today, and let's get started! Your path to a successful career in Data Science with Python begins with us.
 CPD 
100 CPD hours / points  Accredited by CPD Quality Standards
 Who is this course for? 
Beginners with an interest in Data Science and Python programming.
Programmers and Software Engineers looking to transition into Data Science.
Business Analysts and Project Managers aiming to leverage Data Science in their domains.
Researchers and Academics who wish to utilise Python for complex data analysis.
 Requirements 
No experience required. Just enrol & start learning.
 Career path 
Data Scientist: £60,000 - £90,000
Machine Learning Engineer: £65,000 - £100,000
Data Analyst: £40,000 - £60,000
Business Intelligence Analyst: £45,000 - £70,000
Data Engineer: £50,000 - £80,000
Big Data Architect: £70,000 - £120,000
 Certificates 
CPD Accredited e-Certificate
 Digital certificate - Included 
CPD Accredited Framed (Hardcopy) Certificate
 Hard copy certificate - Included 
Enrolment Letter
 Digital certificate - Included 
QLS Endorsed Hard Copy Certificate
 Hard copy certificate - Included 
Student ID Card
 Digital certificate - Included 

Big Data Analytics

Data Science

Data Skills

Data Science with Python - IT Job Ready Program with Career Support & Money Back Guarantee

<strong>You will master the fundamentals and more advanced principles of Python programming in this beginner's tutorial. This Python course covers every Python fundamental, including installation and more complex material such as Python data science.</strong>
        <p>'Python is the future of artificial intelligence and machine learning.'-Adrian Rosebrock, author.

Python is the programming language most loved by developers, data scientists, software engineers, and even hackers.

This Python basic to advanced course covers the fundamental concepts of Python programming and ways to apply this to real-world applications. The course modules, lesson-end quizzes, and lesson-end projects collectively cover the training course topics such as data operations, strings, file I/O, exception handling, error handling, conditional statements, CGI programming, shell scripting, web scraping, and Django.

It also covers Logging Framework, Unittest Framework, Socket Programming, Tornado Framework, and Networking. You will also build a Python chat server.

By the end of this course, you will have the skills to create and send robust Python applications using off-the-rack libraries confidently.

The code bundle for this course is available at: https://github.com/PacktPublishing/Python-Programming</p>
        <h2>What You Will Learn</h2><p>Learn the basics of Python<br>Learn networking and database access using Python and CGI programming<br>Understand the Python debugger<br>Understand web scraping using Beautiful Soup<br>Learn about Python Unittest<br>Build a Python chat server</p>
        <h2>Audience</h2><p>This course is for new Python users looking to make the best of this powerful programming language-college freshers, software developers, programming enthusiasts, and technical leads. Python is widely used in artificial intelligence, so if you are planning to start your career in AI/machine learning then you need to have an understanding of Python as a prerequisite.</p>
        <h2>Approach</h2><p>This course comprises self-paced videos, demos, lesson-end quizzes, and a competitive course-end project. This will help you increase your in-depth understanding of Python's design, memory models, object-arranged highlights, and information, and be industry-prepared.</p>
        <h2>Key Features</h2><p>Go from a beginner level to a confident level of Python programming * Increase your in-depth understanding of Python's design, memory models, and more * Work on a competitive project at the end of the course</p>
        <h2>Github Repo</h2><p>https://github.com/packtpublishing/python-programming</p>
        <h2>About the Author</h2><h3>Learnkart Technology Private Limited</h3><p>Learnkart understands the importance of upskilling and its impact on you. They pride themselves in creating specialized e-learning courses that will not only prepare you for certification exams but also help you gain hands-on knowledge for real-world applications. Thousands of students have developed their skills with Learnkart through a variety of courses, such as PgMP, Risk Management Professional (RMP), speech recognition, Python, Amazon Web Services (AWS), and more. Learnkart regularly adds courses to its portfolio to lend more value to your learning experience.</p>
        <h2>Course Outline</h2><h4>1. Course Introduction</h4><p></p><br><h4>2. Python Basics</h4><p></p><br><h4>3. Data Operations</h4><p></p><br><h4>4. Conditional Statements and Functions</h4><p></p><br><h4>5. Error Handling and File Operations</h4><p></p><br><h4>6. Shell Scripting and Django</h4><p></p><br><h4>7. Course End Project</h4><p></p>

You will master the fundamentals and more advanced principles of Python programming in this beginner's tutorial. This Python course covers every Python fundamental, including installation and more complex material such as Python data science.

Python Programming

Master Python 3.10 from the experts with this course and demonstrate programming wizardry in Python. Go from a geek to a wizard in no time with this well-structured video course and write Python code like a pro. Learn about the often-forgotten basics and special features of programming and Python in general.

The Ultimate Guide to Python Programming with Python 3.10

<p><strong>Start your career as a Data Scientist and earn upto £90,000/ Year</strong></p><p>Are you ready to unlock the power of Python and dive into the exciting world of data science? Look no further because we have the ultimate solution for you: Introducing our Data Science with Python Course with Career Support and Job Ready Program!</p><p><strong>Our mission is simple</strong> - to be your trusted partner every step of the way, from training to employment.</p><p>In addition to teaching you the technical skills you need, we will also provide you with <strong>career mentoring and support</strong>. We will help you build your resume, prepare for interviews, and land your <strong>dream job</strong>. We also have<strong> partnerships with many companies</strong> that are hiring <strong>Data Scientists</strong>, so we can help you get your foot in the door.</p><p>If you are not happy with our service, we also offer a <strong>100% money-back guarantee</strong>. So what are you waiting for? Enrol in our Data Scientist with Python Training Program today and start your journey to becoming a successful Data Scientist!</p><p>If you have any questions, you can <strong>contact us</strong>. We will be happy to provide you with all the information you need.</p><p><strong>Why Choose Us?</strong></p><p>So, what sets us apart from other programs? Let's dive into the exceptional benefits you'll experience when you join our Data Scientist with Python:</p><ul><li><strong>Personalised Guidance:</strong> We believe in the power of individual attention. Our experienced mentors will provide one-on-one counselling sessions tailored to your specific needs. Whether you're a beginner or have some <strong>Data Scientist</strong> experience, we will guide you towards honing your skills and developing a strong foundation in <strong>Data Science</strong>.<br /><br /></li><li><strong>Tailored CV Building:</strong> Crafting an impressive CV is crucial in today's competitive job market. Our team of experts will work closely with you to create a professional CV that showcases your skills and highlights your potential as a Data Scientist. We'll ensure that your CV stands out among the rest, increasing your chances of landing that dream job.<br /><br /></li><li><strong>One-On-One Consultation Sessions with Industry Experts:</strong> Gain invaluable insights and guidance from seasoned professionals who have thrived in the <strong>Data Science</strong> field. Our consultation sessions provide you with insider tips, tricks, and advice, empowering you to navigate the industry with confidence and expertise.<br /><br /></li><li><strong>Extensive Job Opportunities:</strong> We have established partnerships with numerous companies actively seeking Data Scientists. Through our network, we'll connect you with exclusive job openings that are not easily accessible elsewhere. <br /><br /></li><li><strong>Interview Preparation:</strong> No more stress over unexpected interview questions. We provide you with access to a comprehensive database of potential interview questions curated over years of industry experience. Walk into your interviews confident, well-prepared, and ready to impress.<br /><br /></li><li><strong>Money-Back Guarantee:</strong> Your satisfaction is our top priority. We are confident in the quality of our training and support, which is why we offer a <strong>100% money-back guarantee. </strong>If, for any reason, you're not happy with our services, we'll refund your investment, no questions asked. <br /><br /></li><li><strong>Continuous Career Support: </strong>Our commitment doesn't end when you secure a job. We'll be there for you throughout your career journey, offering continued support and guidance. Whether you need advice on career advancement, assistance with new projects, or simply a friendly ear to share your achievements, we'll be your trusted partner for long-term success.</li></ul><p><strong>Here are the courses we will provide once you enrol in the program:</strong></p><ul><li>Course 01: Ultimate Python Training for Beginners</li><li>Course 02: Python Intermediate Training</li><li>Course 03: Python Advanced Training</li><li>Course 04: SQL for Data Science, Data Analytics and Data Visualization</li><li>Course 05: Basic Data Analysis</li><li>Course 06: Develop Big Data Pipelines with R &amp; Sparklyr &amp; Tableau</li><li>Course 07: Develop Big Data Pipelines with R, Sparklyr &amp; Power BI</li><li>Course 08: Customer Analytics Training</li><li>Course 09: Google Analytics for Everyone</li><li>Course 10: Google Data Studio: Data Analytics</li><li>Course 11: Big Data Analytics with PySpark Tableau Desktop and MongoDB</li><li>Course 12: Big Data Analytics with PySpark Power BI and MongoDB</li><li>Course 13: Excel Data Analysis</li><li>Course 14: Introduction to Data Analytics with Tableau</li><li>Course 15: Machine Learning with Python Course</li><li>Course 16: Python Programming Bible | Networking, GUI, Email, XML, CGI</li></ul><p><strong>How Can We Offer Job Guarantees?</strong></p><p>HF Online provides consultancy, professional and educational services to many of the companies in the UK. During our intense exclusive training program, you will not just gain and complete the industry valuable certification but will gain industry experience as well, which is imperative to get your 1st job in the sector.</p> <p><strong>The </strong><strong>Data Scientist with Python </strong><strong>Program is completed in 9 easy steps:</strong></p><p><strong>Step 1: Enrol in the Programme</strong></p><p>Begin your exciting journey with us by enrolling in the <strong>Data Scientist </strong>Training program. Complete your registration and make a secure online payment. Remember, we offer a 14-day money-back guarantee if you're not completely satisfied.</p><p>After you enrol in the Program, you will get lifetime access to 16 premium courses related to <strong>Data Scientist</strong>. These courses will teach you the knowledge and skills required to become a successful Data Scientist. Our customer service team will help you and keep in contact with you every step of the way. So you won't have to worry about a thing!</p><p><strong>Step 2: Initial One-On-One Counselling Session</strong></p><p>Once enrolled, you will be paired with a dedicated career mentor. Schedule your first one-on-one session to discuss your career aspirations, skills, experience, and any areas for potential growth. This conversation will shape your learning and development path.</p><p><strong>Step 3 - </strong><strong>Certification upon Course Completion</strong></p><p>After learning from the courses, you must obtain certificates for each course. There will be exams for every course, and you have to pass them to get your certificate. To pass successfully, you must get 90% marks. Once you pass the exams, you will receive hardcopy certificates. These certificates will prove that you're an expert in the subject.</p><p><strong>Step 4: </strong><strong>CV Revamping</strong></p><p>Our team of professionals will build you a compelling CV and <strong>LinkedIn profile</strong>. We'll ensure it presents your skills and qualifications effectively and is tailored to the needs and expectations of the <strong>Data Scientist</strong> industry. With these powerful tools in hand, you'll be fully prepared to tackle job interviews confidently.</p><p><strong>Step 5: Building Network and Submitting CV</strong></p><p>We understand the power of casting a wide net. We'll strategically submit your CV to various platforms and networks, expanding your reach and connecting you with valuable opportunities that align with your career goals. We will also make connections with many<strong> high-profile individuals and companies</strong> through your LinkedIn profile.</p><p><strong>Step 6: Interview Preparation</strong></p><p>With your CV ready, we'll move on to interview preparation. Gain exclusive access to our database of potential interview questions. Through simulated interviews with your mentor, you'll practice your responses and receive valuable feedback to further refine your skills.</p><p><strong>Step 7: Securing Job Interviews</strong></p><p>Leveraging our partnerships with leading companies, <strong>we'll secure job interviews for you</strong>. We'll ensure you get the opportunity to showcase your skills to potential employers and <strong>get the dream job you want</strong>.</p><p><strong>Step 8: Post-Interview Support</strong></p><p>Post-interview, we'll provide a debriefing session to reflect on your performance and identify areas of improvement for future interviews if necessary. Remember, our commitment extends until you land your dream job.</p><p><strong>Step 9: Celebrate Your New Job!</strong></p><p>Once you've secured your dream job in Data Science, it's time to celebrate! However, our support doesn't end there. We'll provide you with ongoing career advice to ensure you continue to thrive in your new role.</p><p>We're excited to accompany you on this journey to success. Enrol today, and let's get started! Your path to a successful career in <strong>Data Science</strong> begins with us.</p> <h2>
        
        <div>CPD</div>
    </h2>

                        <div id="cpd">
                            <div>
                                <div>
                                    <div>
                                        100 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>Aspiring data scientists looking to enter the exciting field of data science.</li><li>Professionals from other disciplines who want to transition into the data science domain.</li><li>Software engineers or programmers interested in expanding their skill set to include data science.</li><li>Analysts or researchers who want to enhance their data analysis and modeling capabilities.</li><li>Students or graduates seeking to kick-start their careers in data science with a strong foundation.</li></ul>
                        </div> <h2>
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                            <p>No experience required. Just enrol &amp; start learning.</p>
                        </div> <h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                            <ul><li>Data Analyst: £25,000 - £55,000 per year</li><li>Data Scientist: £40,000 - £85,000 per year</li><li>Machine Learning Engineer: £50,000 - £100,000 per year</li><li>Data Engineer: £45,000 - £80,000 per year</li><li>Business Intelligence Analyst: £35,000 - £65,000 per year</li><li>Data Science Manager: £70,000 - £120,000 per year.</li></ul>
                        </div> <h2>
        
        <div>Certificates</div>
    </h2>

                        <div id="optional_extras">
                                    <h4>CPD Accredited e-Certificate</h4>
        <p>
            Digital certificate -
            Included
        </p>
        <h4>CPD Accredited Framed (Hardcopy) Certificate</h4>
        <p>
            Hard copy certificate -
            Included
        </p>
        <h4>Enrolment Letter</h4>
        <p>
            Digital certificate -
            Included
        </p>
        <h4>QLS Endorsed Hard Copy Certificate </h4>
        <p>
            Hard copy certificate -
            Included
        </p>
        <h4>Student ID Card</h4>
        <p>
            Digital certificate -
            Included
        </p>

                        </div>

Start your career as a Data Scientist and earn upto £90,000/ Year
Are you ready to unlock the power of Python and dive into the exciting world of data science? Look no further because we have the ultimate solution for you: Introducing our Data Science with Python Course with Career Support and Job Ready Program!
Our mission is simple - to be your trusted partner every step of the way, from training to employment.
In addition to teaching you the technical skills you need, we will also provide you with career mentoring and support. We will help you build your resume, prepare for interviews, and land your dream job. We also have partnerships with many companies that are hiring Data Scientists, so we can help you get your foot in the door.
If you are not happy with our service, we also offer a 100% money-back guarantee. So what are you waiting for? Enrol in our Data Scientist with Python Training Program today and start your journey to becoming a successful Data Scientist!
If you have any questions, you can contact us. We will be happy to provide you with all the information you need.
Why Choose Us?
So, what sets us apart from other programs? Let's dive into the exceptional benefits you'll experience when you join our Data Scientist with Python:
Personalised Guidance: We believe in the power of individual attention. Our experienced mentors will provide one-on-one counselling sessions tailored to your specific needs. Whether you're a beginner or have some Data Scientist experience, we will guide you towards honing your skills and developing a strong foundation in Data Science.
Tailored CV Building: Crafting an impressive CV is crucial in today's competitive job market. Our team of experts will work closely with you to create a professional CV that showcases your skills and highlights your potential as a Data Scientist. We'll ensure that your CV stands out among the rest, increasing your chances of landing that dream job.
One-On-One Consultation Sessions with Industry Experts: Gain invaluable insights and guidance from seasoned professionals who have thrived in the Data Science field. Our consultation sessions provide you with insider tips, tricks, and advice, empowering you to navigate the industry with confidence and expertise.
Extensive Job Opportunities: We have established partnerships with numerous companies actively seeking Data Scientists. Through our network, we'll connect you with exclusive job openings that are not easily accessible elsewhere.
Interview Preparation: No more stress over unexpected interview questions. We provide you with access to a comprehensive database of potential interview questions curated over years of industry experience. Walk into your interviews confident, well-prepared, and ready to impress.
Money-Back Guarantee: Your satisfaction is our top priority. We are confident in the quality of our training and support, which is why we offer a 100% money-back guarantee. If, for any reason, you're not happy with our services, we'll refund your investment, no questions asked.
Continuous Career Support: Our commitment doesn't end when you secure a job. We'll be there for you throughout your career journey, offering continued support and guidance. Whether you need advice on career advancement, assistance with new projects, or simply a friendly ear to share your achievements, we'll be your trusted partner for long-term success.
Here are the courses we will provide once you enrol in the program:
Course 01: Ultimate Python Training for Beginners
Course 02: Python Intermediate Training
Course 03: Python Advanced Training
Course 04: SQL for Data Science, Data Analytics and Data Visualization
Course 05: Basic Data Analysis
Course 06: Develop Big Data Pipelines with R & Sparklyr & Tableau
Course 07: Develop Big Data Pipelines with R, Sparklyr & Power BI
Course 08: Customer Analytics Training
Course 09: Google Analytics for Everyone
Course 10: Google Data Studio: Data Analytics
Course 11: Big Data Analytics with PySpark Tableau Desktop and MongoDB
Course 12: Big Data Analytics with PySpark Power BI and MongoDB
Course 13: Excel Data Analysis
Course 14: Introduction to Data Analytics with Tableau
Course 15: Machine Learning with Python Course
Course 16: Python Programming Bible | Networking, GUI, Email, XML, CGI
How Can We Offer Job Guarantees?
HF Online provides consultancy, professional and educational services to many of the companies in the UK. During our intense exclusive training program, you will not just gain and complete the industry valuable certification but will gain industry experience as well, which is imperative to get your 1st job in the sector.
The Data Scientist with Python Program is completed in 9 easy steps:
Step 1: Enrol in the Programme
Begin your exciting journey with us by enrolling in the Data Scientist Training program. Complete your registration and make a secure online payment. Remember, we offer a 14-day money-back guarantee if you're not completely satisfied.
After you enrol in the Program, you will get lifetime access to 16 premium courses related to Data Scientist. These courses will teach you the knowledge and skills required to become a successful Data Scientist. Our customer service team will help you and keep in contact with you every step of the way. So you won't have to worry about a thing!
Step 2: Initial One-On-One Counselling Session
Once enrolled, you will be paired with a dedicated career mentor. Schedule your first one-on-one session to discuss your career aspirations, skills, experience, and any areas for potential growth. This conversation will shape your learning and development path.
Step 3 - Certification upon Course Completion
After learning from the courses, you must obtain certificates for each course. There will be exams for every course, and you have to pass them to get your certificate. To pass successfully, you must get 90% marks. Once you pass the exams, you will receive hardcopy certificates. These certificates will prove that you're an expert in the subject.
Step 4: CV Revamping
Our team of professionals will build you a compelling CV and LinkedIn profile. We'll ensure it presents your skills and qualifications effectively and is tailored to the needs and expectations of the Data Scientist industry. With these powerful tools in hand, you'll be fully prepared to tackle job interviews confidently.
Step 5: Building Network and Submitting CV
We understand the power of casting a wide net. We'll strategically submit your CV to various platforms and networks, expanding your reach and connecting you with valuable opportunities that align with your career goals. We will also make connections with many high-profile individuals and companies through your LinkedIn profile.
Step 6: Interview Preparation
With your CV ready, we'll move on to interview preparation. Gain exclusive access to our database of potential interview questions. Through simulated interviews with your mentor, you'll practice your responses and receive valuable feedback to further refine your skills.
Step 7: Securing Job Interviews
Leveraging our partnerships with leading companies, we'll secure job interviews for you. We'll ensure you get the opportunity to showcase your skills to potential employers and get the dream job you want.
Step 8: Post-Interview Support
Post-interview, we'll provide a debriefing session to reflect on your performance and identify areas of improvement for future interviews if necessary. Remember, our commitment extends until you land your dream job.
Step 9: Celebrate Your New Job!
Once you've secured your dream job in Data Science, it's time to celebrate! However, our support doesn't end there. We'll provide you with ongoing career advice to ensure you continue to thrive in your new role.
We're excited to accompany you on this journey to success. Enrol today, and let's get started! Your path to a successful career in Data Science begins with us.
 CPD 
100 CPD hours / points  Accredited by CPD Quality Standards
 Who is this course for? 
Aspiring data scientists looking to enter the exciting field of data science.
Professionals from other disciplines who want to transition into the data science domain.
Software engineers or programmers interested in expanding their skill set to include data science.
Analysts or researchers who want to enhance their data analysis and modeling capabilities.
Students or graduates seeking to kick-start their careers in data science with a strong foundation.
 Requirements 
No experience required. Just enrol & start learning.
 Career path 
Data Analyst: £25,000 - £55,000 per year
Data Scientist: £40,000 - £85,000 per year
Machine Learning Engineer: £50,000 - £100,000 per year
Data Engineer: £45,000 - £80,000 per year
Business Intelligence Analyst: £35,000 - £65,000 per year
Data Science Manager: £70,000 - £120,000 per year.
 Certificates 
CPD Accredited e-Certificate
 Digital certificate - Included 
CPD Accredited Framed (Hardcopy) Certificate
 Hard copy certificate - Included 
Enrolment Letter
 Digital certificate - Included 
QLS Endorsed Hard Copy Certificate
 Hard copy certificate - Included 
Student ID Card
 Digital certificate - Included 

Data Analyst

Data Scientist with Python - IT Job Ready Program + Career Support & Money Back Guarantee

<strong>This course offers you the exact skills and principles you need to deliver a project using Python along with the tools you can use to create solid Python code. Master the language constructs, tools, and terminology with this carefully designed course for beginners.</strong>
        <p>Python is one of the most popular computer programming languages and this hands-on course for beginners will make it easy for someone who wants to get started with learning Python.

This course takes you through the introduction to the course and the learning objectives. You will learn to get started with Replit and write your first Python program. You will learn to store, process, and compare information in Python as well as learn to tidy messy data. You will learn about variables, strings, dictionaries, indexing, and slicing in Python. Further, you will understand loops in Python along with break, continue, and else functions.

Moving ahead, you will understand error handling in Python, get to know the try-and-catch block, and learn to add resources to Replit. You will also understand function parameters and explore the difference between local and global variables, and positional and keyword parameters. You will learn to work with JSON and clean the data along with various numeric functions such as min, max, and sum.

By the end of the course, you will gain a solid foundation in Python programming and be able to write high-quality code in Python.

All resources and code files are placed here: https://github.com/PacktPublishing/Python-Bootcamp-in-a-day---Python-Programming-for-Beginners</p>
        <h2>What You Will Learn</h2><p>Master Python programming fundamentals<br>Learn how to install Python to get up and running in no time<br>Learn how to process data to create Olympics Medals Tables<br>Solve multiple specific problems for a customer in the real world<br>Learn all about objects and variables in Python<br>Understand functions and function parameters in Python</p>
        <h2>Audience</h2><p>Whether you are a software engineer, software developer, computer programmer, web developer, transitioning into a new role, or simply someone who wants to understand what makes Python tick, this is the place to start. If you are preparing for a Python certification or job role, this course is for you.</p>
        <h2>Approach</h2><p>This course is video based course with no supporting document necessary. It takes you through the fundamentals of Python and teaches you how to use it with a simple tool so you can master the fundamentals in a day.</p>
        <h2>Key Features</h2><p>Be fluent in writing Python code and working with all the fundamentals of the language such as a list, string, function, dictionary, array, set, and much more * Learn to use Python's data analysis capabilities to analyze data from a real-world data source * A complete overview of the basics with exercises to test your knowledge of storing, processing, and storing information</p>
        <h2>Github Repo</h2><p>https://github.com/PacktPublishing/Python-Bootcamp-in-a-day---Python-Programming-for-Beginners</p>
        <h2>About the Author</h2><h3>Paul Ashun</h3><p>Paul Ashun is the CEO, MD, and chief consultant at Pashun Consulting Ltd., specializing in Scrum coaching and leadership within major global organizations. They are the authors of over 10 books on Scrum such as The Power of Scrum in the Real World, Confessions of a Scrum Master as well as the upcoming Agile User Storybook.

He started as a software developer and over ten years later, he became an Agile portfolio manager. He is a certified Scrum Master and a PMO manager. He has led projects for the BBC, General Electric, Oracle, BSkyB, HiT Entertainment, and Razorfish. He has been coaching product owners and business analysts in international blue-chip companies, dating back to 1999, in Agile and Scrum practices such as writing user stories.</p>
        <h2>Course Outline</h2><h4>1. Introduction</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Introduction</p><p style='margin: 0'>This video is an introduction the course and what you can expect from the course.</p></td></tr><tr><td style='padding: 15px;'><p>2. Learning Objectives - Introduction</p><p style='margin: 0'>This video explains the learning objectives of the course.</p></td></tr><tr><td style='padding: 15px;'><p>3. What Is Python?</p><p style='margin: 0'>This video explains what Python is and the need for Python.</p></td></tr><tr><td style='padding: 15px;'><p>4. The Example</p><p style='margin: 0'>This video explains an example of a software engineer working in a media company to support the development team.</p></td></tr></tbody></table><br><h4>2. Getting Set Up</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Learning Objectives - Getting Set Up</p><p style='margin: 0'>This video explains the learning objectives of this section.</p></td></tr><tr><td style='padding: 15px;'><p>2. How to Get Started with Replit</p><p style='margin: 0'>This video explains how to get started with Replit.</p></td></tr><tr><td style='padding: 15px;'><p>3. Writing Your First Python Program-Hello World</p><p style='margin: 0'>This video explains writing your first Python program-Hello World.</p></td></tr></tbody></table><br><h4>3. Storing Information</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Learning Objectives - Storing Information</p><p style='margin: 0'>This video explains the learning objectives of this section.</p></td></tr><tr><td style='padding: 15px;'><p>2. Objects and Variables</p><p style='margin: 0'>This video explains objects and variables in Python using an example of Olympic results.</p></td></tr><tr><td style='padding: 15px;'><p>3. Variable Names</p><p style='margin: 0'>This video explains variable names in Python and the rules to use them.</p></td></tr><tr><td style='padding: 15px;'><p>4. Numbers</p><p style='margin: 0'>This video explains the different types of numbers in Python.</p></td></tr><tr><td style='padding: 15px;'><p>5. Strings</p><p style='margin: 0'>This video explains strings in Python.</p></td></tr><tr><td style='padding: 15px;'><p>6. Showing Output When Running Python</p><p style='margin: 0'>This video explains showing output when running Python.</p></td></tr></tbody></table><br><h4>4. Processing Information</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Learning Objectives - Processing Information</p><p style='margin: 0'>This video explains the learning objectives of the section.</p></td></tr><tr><td style='padding: 15px;'><p>2. Processing Information</p><p style='margin: 0'>This video explains processing information in Python.</p></td></tr><tr><td style='padding: 15px;'><p>3. Indexing</p><p style='margin: 0'>This video explains indexing in Python.</p></td></tr><tr><td style='padding: 15px;'><p>4. Slices</p><p style='margin: 0'>This video explains slices in Python.</p></td></tr><tr><td style='padding: 15px;'><p>5. String Functions</p><p style='margin: 0'>This video explains string functions in Python.</p></td></tr><tr><td style='padding: 15px;'><p>6. The 'input' Function</p><p style='margin: 0'>This video explains the input function in Python.</p></td></tr><tr><td style='padding: 15px;'><p>7. More String Operations</p><p style='margin: 0'>This video explains more string operations in Python.</p></td></tr><tr><td style='padding: 15px;'><p>8. Converting Between Different Types</p><p style='margin: 0'>This video explains converting between different types.</p></td></tr></tbody></table><br><h4>5. Comparing Information</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Learning Objectives - Comparing Information</p><p style='margin: 0'>This video explains the learning objectives of this section.</p></td></tr><tr><td style='padding: 15px;'><p>2. Comparing Information</p><p style='margin: 0'>This video explains comparing information in Python.</p></td></tr></tbody></table><br><h4>6. Tidying Messy Data</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Learning Objectives - Tidying Messy Data</p><p style='margin: 0'>This video explains the learning objectives of this section.</p></td></tr><tr><td style='padding: 15px;'><p>2. Tidying Messy Data</p><p style='margin: 0'>This video explains how to tidy messy data.</p></td></tr></tbody></table><br><h4>7. Storing Multiple Things</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Learning Objectives - Storing Multiple Things</p><p style='margin: 0'>This video explains the learning objectives of this section.</p></td></tr><tr><td style='padding: 15px;'><p>2. Storing Multiple Things</p><p style='margin: 0'>This video explains how to store multiple things.</p></td></tr><tr><td style='padding: 15px;'><p>3. Introducing Python Lists</p><p style='margin: 0'>This video explains lists in Python.</p></td></tr><tr><td style='padding: 15px;'><p>4. Adding Items to a List</p><p style='margin: 0'>This video explains how to add items to a list.</p></td></tr><tr><td style='padding: 15px;'><p>5. Indexing and Slicing Lists</p><p style='margin: 0'>This video explains indexing and slicing lists.</p></td></tr><tr><td style='padding: 15px;'><p>6. Deleting Items in a List</p><p style='margin: 0'>This video explains how to delete items in a list.</p></td></tr><tr><td style='padding: 15px;'><p>7. Tuples</p><p style='margin: 0'>This video explains tuples in Python.</p></td></tr><tr><td style='padding: 15px;'><p>8. Long Lines in Python</p><p style='margin: 0'>This video explains long lines in Python.</p></td></tr><tr><td style='padding: 15px;'><p>9. Dictionaries</p><p style='margin: 0'>This video explains dictionaries in Python.</p></td></tr><tr><td style='padding: 15px;'><p>10. List Functions - More Ways to Work with Lists</p><p style='margin: 0'>This video explains list functions.</p></td></tr><tr><td style='padding: 15px;'><p>11. Sets</p><p style='margin: 0'>This video explains sets in Python.</p></td></tr></tbody></table><br><h4>8. Processing Collections</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Learning Objectives - Processing Collections</p><p style='margin: 0'>This video explains the learning objectives of the section.</p></td></tr><tr><td style='padding: 15px;'><p>2. A Simple 'for' Loop</p><p style='margin: 0'>This video explains a simple for loop.</p></td></tr><tr><td style='padding: 15px;'><p>3. More Complex 'for' loops - 'break', 'continue', and 'else'</p><p style='margin: 0'>This video explains more complex 'for' loops.</p></td></tr><tr><td style='padding: 15px;'><p>4. The 'range' Function - How to Create a List of Numbers</p><p style='margin: 0'>This video explains how to create a list of numbers.</p></td></tr><tr><td style='padding: 15px;'><p>5. The 'while' Loop - Do Something for a While</p><p style='margin: 0'>This video explains the while loop.</p></td></tr></tbody></table><br><h4>9. Robust Programs - Handling Errors</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Learning Objectives - Robust Programs - Handling Errors</p><p style='margin: 0'>This video explains the learning objectives of the section.</p></td></tr><tr><td style='padding: 15px;'><p>2. Robust Programs - Handling Errors</p><p style='margin: 0'>This video explains error handling in Python.</p></td></tr><tr><td style='padding: 15px;'><p>3. Look Before You Leap</p><p style='margin: 0'>This video explains one way of making the code more robust, which is called 'look before you leap'.</p></td></tr><tr><td style='padding: 15px;'><p>4. The Try and Except Block</p><p style='margin: 0'>This video explains the try and except block in Python.</p></td></tr><tr><td style='padding: 15px;'><p>5. The Catch-All Block</p><p style='margin: 0'>This video explains the catch-all block.</p></td></tr><tr><td style='padding: 15px;'><p>6. Adding Resources to Replit</p><p style='margin: 0'>This video explains how to add resources to Replit.</p></td></tr><tr><td style='padding: 15px;'><p>7. The Finally Block</p><p style='margin: 0'>This video explains the finally block.</p></td></tr></tbody></table><br><h4>10. Saving the Results - Working with Files</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Learning Objectives - Saving the Results - Working with Files</p><p style='margin: 0'>This video explains the learning objectives of the course.</p></td></tr><tr><td style='padding: 15px;'><p>2. Adding Bad Data</p><p style='margin: 0'>This video explains adding bad data.</p></td></tr><tr><td style='padding: 15px;'><p>3. Saving the Results - Working with Files</p><p style='margin: 0'>This video explains saving the results and working with files.</p></td></tr><tr><td style='padding: 15px;'><p>4. Binary File Modes</p><p style='margin: 0'>This video explains binary file modes.</p></td></tr><tr><td style='padding: 15px;'><p>5. Text File Modes</p><p style='margin: 0'>This video explains text file modes.</p></td></tr><tr><td style='padding: 15px;'><p>6. The With Statement</p><p style='margin: 0'>This video explains the with statement.</p></td></tr></tbody></table><br><h4>11. Breaking Up Larger Programs, Part 1</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Learning Objectives - Breaking Up Larger Programs, Part 1</p><p style='margin: 0'>This video explains the learning objectives of the section.</p></td></tr><tr><td style='padding: 15px;'><p>2. About Replit.config</p><p style='margin: 0'>This video explains replit.config.</p></td></tr><tr><td style='padding: 15px;'><p>3. Functions</p><p style='margin: 0'>This video explains functions in Python.</p></td></tr><tr><td style='padding: 15px;'><p>4. Function Parameters</p><p style='margin: 0'>This video explains function parameters.</p></td></tr><tr><td style='padding: 15px;'><p>5. Local Versus Global Variables</p><p style='margin: 0'>This video explains local versus global variables.</p></td></tr><tr><td style='padding: 15px;'><p>6. Positional and Keyword Parameters</p><p style='margin: 0'>This video explains positional and keyword parameters.</p></td></tr><tr><td style='padding: 15px;'><p>7. Return Statement</p><p style='margin: 0'>This video explains the return statement.</p></td></tr><tr><td style='padding: 15px;'><p>8. Working With JSON</p><p style='margin: 0'>This video explains working with JSON.</p></td></tr><tr><td style='padding: 15px;'><p>9. Code Comments and Clear Code</p><p style='margin: 0'>This video explains code comments in Python.</p></td></tr></tbody></table><br><h4>12. Summarising and Presenting the Results</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Learning Objectives - Summarising and Presenting the Results</p><p style='margin: 0'>This video explains the learning objectives of the section.</p></td></tr><tr><td style='padding: 15px;'><p>2. Summarising and Presenting the Results Part 1</p><p style='margin: 0'>This video explains how to summarise the results using statistics.</p></td></tr><tr><td style='padding: 15px;'><p>3. Cleaning the Data</p><p style='margin: 0'>This video explains cleaning the data in Python.</p></td></tr><tr><td style='padding: 15px;'><p>4. Summarising and Presenting the Results Part 2</p><p style='margin: 0'>This video explains the code in which we will get a sum of the scores of a country.</p></td></tr><tr><td style='padding: 15px;'><p>5. More Numeric Functions - Min, Max, Sum</p><p style='margin: 0'>This video explains min, max, and sum functions in Python.</p></td></tr><tr><td style='padding: 15px;'><p>6. Formatted Strings, f-strings</p><p style='margin: 0'>This video explains formatted strings and f-strings in Python.</p></td></tr></tbody></table><br><h4>13. Breaking Up Larger Programs, Part 2</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Learning Objectives - Breaking Up Larger Programs, Part 2</p><p style='margin: 0'>This video explains the learning objectives of the section.</p></td></tr><tr><td style='padding: 15px;'><p>2. Splitting Code into Modules</p><p style='margin: 0'>This video explains splitting code into modules.</p></td></tr><tr><td style='padding: 15px;'><p>3. Namespaces</p><p style='margin: 0'>This video explains namespaces in Python.</p></td></tr><tr><td style='padding: 15px;'><p>4. Using Our Modules</p><p style='margin: 0'>This video explains how to use modules in Python.</p></td></tr></tbody></table><br><h4>14. Getting Set Up on a PC or MAC</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Learning Objectives - Getting Set Up on a PC or MAC</p><p style='margin: 0'>This video explains the learning objectives of the section.</p></td></tr><tr><td style='padding: 15px;'><p>2. Getting Set Up</p><p style='margin: 0'>This video explains how to set up Python on our systems.</p></td></tr><tr><td style='padding: 15px;'><p>3. Starting Python on Windows 10</p><p style='margin: 0'>This video explains how to start Python on Windows 10.</p></td></tr><tr><td style='padding: 15px;'><p>4. Starting a Terminal or Command Prompt on Windows</p><p style='margin: 0'>This video explains how to start a terminal or command prompt on Windows.</p></td></tr><tr><td style='padding: 15px;'><p>5. Installing Python on Windows</p><p style='margin: 0'>This video explains the installation of Python on Windows.</p></td></tr><tr><td style='padding: 15px;'><p>6. Installing Python on MacOS</p><p style='margin: 0'>This video explains the installation on Python on MacOS.</p></td></tr><tr><td style='padding: 15px;'><p>7. Quick Python Test - Running Python</p><p style='margin: 0'>This video explains how to run a Python script.</p></td></tr><tr><td style='padding: 15px;'><p>8. Python Scripts and IDLE</p><p style='margin: 0'>This video explains Python scripts and IDE.</p></td></tr><tr><td style='padding: 15px;'><p>9. Code Editors and IDEs</p><p style='margin: 0'>This video explains code editors and IDEs.</p></td></tr><tr><td style='padding: 15px;'><p>10. Running Python Scripts</p><p style='margin: 0'>This video explains how to run Python scripts.</p></td></tr></tbody></table>

This course offers you the exact skills and principles you need to deliver a project using Python along with the tools you can use to create solid Python code. Master the language constructs, tools, and terminology with this carefully designed course for beginners.

Python Bootcamp in a Day - Python Programming for Beginners.

Network

Networking

Cisco

This course is an excellent resource to learn network programming using Python. With the help of practical examples, you will learn how to automate networks with Telnet, Secure Shell (SSH), Paramiko, Netmiko, and Network Automation and Programmability Abstraction Layer with Multivendor support (NAPALM).

Python Network Programming for Network Engineers (Python 3)

<p><strong>Introducing Coding using Python</strong></p>
<p>This course introduces your child to a very advanced, yet easy to learn programming languages &ndash; Python. It&rsquo;s safe to say that many apps we use today have been built using Python &ndash; Instagram Web, Netflix, YouTube, to name a few! This course teaches the fundamentals of coding, and creates a solid foundation to solve more complex real-life problems.</p>

Riva Learning

Programming Languages

Computing

Choose this course if your child is new to Python or has done a few hours of Python before. Or, they have a good understanding of block-based platforms like Scratch, and would like to start exploring text-based programming languages.

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