
Accelerate software development with GitHub Copilot through prompt engineering and context processing. Build Python, React.js, and Springboot in VSCode and IntelliJ, and master unit testing, selenium automation, and postman collections.
Accelerate coding with an AI driven code completion tool by GitHub and OpenAI, powering real-time code suggestions across languages and frameworks, built on Codex and GPT-4 as a learning assistant.
Encourage students to leave optional Udemy ratings and comments on lectures, helping others decide if the course fits them and guiding improvements by highlighting the most helpful parts.
Explore GitHub Copilot's key features—autocomplete, inline chat, chat window, and terminal usage—through Csvparser and fast-csv based csv formatting and a real-time chat app with express and socket.io.
Sign in to github.com, subscribe to GitHub Copilot with a monthly or yearly plan and a 30-day trial, then install Copilot into your IDEs.
Install and activate GitHub Copilot and Copilot chat in Visual Studio Code by navigating to Preferences > Extensions, then use Copilot in the editor to accelerate your code development.
Install the GitHub Copilot plugin into IntelliJ from the plugins marketplace, restart the IDE when prompted, and start using the Copilot chat window to accelerate coding.
Leverage GitHub Copilot to scaffold a Python REST app within Visual Studio, create a modular product CRUD service with a persistent database and REST endpoints, and manage dependencies with pip.
Turn folders into Python modules by adding init.py files for seamless cross-module imports and modularity. Leverage GitHub Copilot and PowerShell commands to restructure directories and automate module creation.
Centralize app and database initialization by moving logic to init.py, tie SQLAlchemy to the app lifecycle, and register product routes on startup with main.py updated.
Upgrade Python libraries with GitHub Copilot, update requirements.txt, and launch a Flask CRUD app locally. Test create, read, update, and delete operations using curl commands.
Scaffold a ReactJS application atop a Python backend with GitHub Copilot, using Accelerate Workspace to generate code, unit tests, and selenium scripts for a modular product app with CRUD features.
Enhance a ReactJS app by adding a product route with react-router-dom, guided by Copilot's import suggestions and patterns. Use the readme to structure the project and launch the app.
Copilot enables a single product form in a React.js app to create or update products using a use effect hook and a conditional submit handler.
Enhance a React app's UI by integrating Bootstrap and transforming the product list into a table with create, edit, and delete actions, using Copilot to update routing and navigation.
Learn real-time debugging with GitHub Copilot in your IDE, as it analyzes terminal errors and provides inline fixes, guiding you to resolve issues like unclosed tags and restart npm start.
Automate unit test creation with GitHub Copilot to write tests for product service using jest fetch mock, covering get products, get product, create product, update product, and delete product.
Accelerate qa with Selenium-driven front-end tests performing CRUD on a React app, guided by Copilot prompts and explicit wait conditions for element presence on localhost 3000.
Adapt selenium automation scripts for Java or NodeJS using Copilot prompts, specify language, import libraries, and follow step-by-step guidance to run the application.
Leverage AI-assisted coding with GitHub Copilot to scaffold a Java Spring Boot app in IntelliJ using Gradle and an H2 database, exposing a books CRUD REST API with controller-service-repository architecture.
Implement sorting, filtering, and pagination for the get all books endpoint using Copilot. Extend the repository with JPA specification executor and add predicate-based criteria for title and author.
Leverage Copilot to implement exporting book data to Excel in a Java app using Apache POI, exposing an endpoint to download books as an Excel file.
Demonstrates writing unit tests with Copilot for controller and service layers, including a new Excel file method, then debugging and fixing tests by adjusting mocks to handle any specification.
Accelerate API documentation by integrating Swagger with GitHub Copilot, automatically document endpoints and models, configure a Swagger config in Spring, and explore Swagger UI for testing endpoints.
Use GitHub Copilot to simplify Excel file code by extracting header and book rows into separate methods, shortening the main create Excel file method, and improving readability.
Explore using GitHub Copilot to implement JWT based authentication and Docker containerization in a Spring Boot microservices app, outlining tokens, claims, roles, and secured endpoints.
Set up SQL Tools in Visual Studio Code to enable Copilot-supported database editing, install the SQL Tools extension from the references, and configure a connection to an Oracle database.
Install the Oracle driver for SQLTools by adding the SQLTools for Oracle extension, then connect to Oracle Database through Visual Studio Code.
Configure SQL tools to connect to an Oracle database by adding a new connection, selecting the Oracle driver, naming it Copilot demo, using port 1521, and testing the connection.
Create a products table in an Oracle database using Copilot in VS Code, with id as auto-generated primary key and fields name, description, price, quantity, created_at timestamp.
Use the inline chat editor to create an index on the products.name column and verify its creation, then add a price check constraint to ensure price is greater than zero.
Use the inline chat editor to fix syntax errors with GitHub Copilot, identify a typo in a constraint name, and accept suggested corrections to resolve the issue.
Create a sku table with an auto-generated primary key ID and a foreign key product_id referencing the products table, including description, price, quantity, and created_at.
Generate test data with mockaroo by defining schemas for names, addresses, and numbers; export as csv, json, or sql; create a products dataset with id, price constraints, and 1000 records.
Generate test data for the skew table, creating a foreign key product id and an auto-generated id, distributing ten skus across products. Preview and import the data.
Leverage GitHub Copilot to generate a SQL*Loader script that loads a CSV of product data into the products table (name, description, price, quantity) with an auto-generated id.
Load skew data into the skew table from a csv using sql*loader, with columns product ID, description, and quantity, fields terminated by comma and optionally enclosed by double quotes.
Learn how to create and run a PL/SQL procedure to add a new product using Copilot's chat, validate results, and drop the procedure.
Leverage Copilot to add a price validation check in a pl sql block, raising an application error when price is less than or equal to zero, then compile and test.
Learn how to write a function that returns data by ID, print results to the console, and iterate a cursor to handle multiple SKUs, with Copilot assisting error handling.
learn how inner join, left outer join, right outer join, and full outer joins work on products and SKUs in Oracle Database, with examples of matching rows and nulls.
Explore creating subqueries and common table expressions with GitHub Copilot to fetch smartphone products, count category products with joins, and build hierarchical category structures.
Leverage GitHub Copilot to scaffold a selenium automation app on herokuapp, creating dedicated test files for login, dropdown, dynamic loading, and file upload with supporting page files.
Use GitHub Copilot to update dependencies and implement login tests with mocha and chai, then run Selenium-driven tests validating successful and failed logins on the Heroku app.
Learn to automate dropdown functionality tests for a Heroku app using Mocha and Selenium WebDriver in JavaScript, validating option one and option two via a page object model.
Accelerate testing of dynamic loading pages with GitHub Copilot, Selenium WebDriver, and Mocha by completing the dynamic loading test.js and validating hidden and post-load elements.
Automate file upload tests for the Heroku app with Selenium WebDriver, with Copilot prompts, locating input and upload elements, uploading a file, and verifying the success message and file name.
Explore Cloud Code, the entropy intelligent coding assistant, that accelerates development, improves code quality, and enhances collaboration across writing, reviewing, and debugging in your full lifecycle.
Explore Claude Code architecture from the user interface through the core application, AI integration, data storage, tool systems, and external services as it enables planning, implementing, and deploying Google login.
Install Claude Code by configuring a macOS terminal, creating a cloud code project, installing via npm globally, signing in, and setting preferences to enable the cloud CLI.
Set up cloud code by creating a project root and subdirectories, install cloud code globally with npm, and run Claude code extension to initialize the IDE extension.
Create a Python expense tracker with cloud code, building a project structure, an expense class, and a cli to add, view, and save expenses to a json file.
Explore the cloud skills ecosystem, where modular, reusable capabilities extend cloud functionality and load from a skills directory. Learn definitions, types, architecture, deployment, and how MCP and agents compare.
Explore the step-by-step architecture of skill loading, from startup prompts with lightweight metadata to invoking the PDF processing skill and loading only what is needed into the context window.
Create a valid skills markdown file from scratch following yammer front matter rules, then install, test, and debug skills in cloud code using a common missed layout scenario.
Explore the skills anatomy and front matter, focusing on YAML front matter with name and description, the body Claude reads, and crafting precise what and when triggers for skills.
Explore design principle skill patterns, including template, example, and workflow patterns, with fixed structures, input-output pairs, and a copyable checklist for multi-step workflows.
June 26, 2026 - Agent Skills
This GitHub Copilot Course transforms your software development workflow with this end-to-end Generative AI Programming Bootcamp, designed to help you become a 10X more productive developer using GitHub Copilot, Amazon Q, Claude Code, and MCP architecture. Whether you’re a Python developer, Java Spring Boot engineer, ReactJS frontend developer, PL/SQL programmer, Selenium automation tester, or AWS cloud engineer, this course shows you how to accelerate every part of the development lifecycle using AI-powered coding tools.
Master generative AI for developers with hands-on projects in Python application scaffolding, ReactJS component development, Java enterprise applications, database programming with AI assistance, automated testing with Selenium, and AWS CLI automation. Learn prompt engineering techniques for optimal AI code generation, automated unit testing, integration testing, and deployment automation.
Perfect for software developers, full-stack engineers, DevOps engineers, QA automation testers, and programming beginners wanting to leverage artificial intelligence tools for accelerated software development. Course includes real-world projects, AI coding best practices, and comprehensive training in GitHub Copilot, Amazon Q developer assistant, and generative AI programming workflows.
Complete AI Development Mastery - What You'll Learn:
GitHub Copilot & Amazon Q Fundamentals
AI pair programming with GitHub Copilot for faster code development
Amazon Q developer assistant for AWS cloud development and troubleshooting
Generative AI prompt engineering for optimal code generation
AI code completion and intelligent code suggestions
Machine learning for developers - practical AI coding applications
Python Development with AI Assistance
Python application scaffolding using GitHub Copilot auto-generation
Automated Python code writing with AI-powered suggestions
Python unit testing automation using generative AI tools
Python debugging with artificial intelligence assistance
Flask and Django development accelerated by AI coding tools
Java & Spring Boot AI Development
Spring Boot application creation with GitHub Copilot assistance
Java enterprise development using AI code generation
RESTful API development with automated code completion
Java unit testing and integration testing with AI tools
Maven and Gradle project management with AI assistance
ReactJS & Frontend Development
React component development using AI-powered code generation
JavaScript ES6+ programming with GitHub Copilot assistance
Frontend testing automation with AI-generated test cases
React hooks and state management using AI coding assistance
API integration and axios configuration with AI tools
Database Development & PL/SQL
SQL query optimization using AI-powered suggestions
PL/SQL procedure development with GitHub Copilot assistance
Database schema design using artificial intelligence tools
Oracle database programming with AI code generation
Database testing automation and performance optimization
Selenium Test Automation
Selenium WebDriver automation with AI-generated test scripts
Cross-browser testing using AI-powered test case creation
Page Object Model implementation with GitHub Copilot
TestNG and JUnit integration with AI assistance
Automated regression testing using generative AI tools
AWS Cloud Development
AWS CLI automation with Amazon Q assistance
Cloud infrastructure setup using AI-powered guidance
AWS services integration with AI coding assistance
Cloud cost optimization using Amazon Q insights
DevOps automation with AI-generated scripts
MCP
MCP Architecture
MCP Server Components and Transport Types
MCP Flow - Server, Client and Host communication over Transport layer
MCP Hands On
Claude Code
Claude Code Installation
Claude Code Architecture
Claude Code - Slash Commands
Claude Code - Memory
Claude Code - MCP
Claude Code - Sub Agents
Claude Code - GitHub Workflow
Claude Code - Agent Skill
Claude Code - Hooks
Through practical examples and hands-on exercises, you will reinforce your learning and gain the confidence to apply these skills in real-world scenarios. Expert guidance from experienced instructors will support you throughout the course, and you'll have the opportunity to join a community of learners for sharing experiences, asking questions, and collaborating on projects.
By the end of this course, you'll be proficient in using GitHub Copilot and Amazon Q to enhance your coding productivity, integrate new technologies efficiently, and follow best practices for code management and collaboration. Join us and take your development skills to the next level!