Github copilot , Spring boot and Spring AI Course Syllabus

Overview: This course is designed for Java developers looking to enhance their Spring Boot productivity using GitHub Copilot. Through hands-on modules, you'll learn to automate boilerplate code, improve code quality, and integrate security and testing best practices with AI assistance. The course spans approximately 3 hours of content, combining conceptual learning with practical implementation to streamline daily development workflows.

Module 1: Introduction to Copilot & Spring Boot

Estimated time: 0.5 hours

• Set up GitHub Copilot in your IDE (VS Code, IntelliJ)
• Integrate Copilot with a Spring Boot project
• Learn fundamental Copilot features: autocomplete, revisions, and context prompts

Module 2: Generating Boilerplate Code

Estimated time: 1 hours

• Use Copilot for rapid scaffolding of application entry points
• Generate model classes and JPA entities
• Create REST controllers with AI assistance
• Automate repetitive code patterns in Spring Boot

Module 3: Context-Aware Refactoring

Estimated time: 0.75 hours

• Apply Copilot suggestions for code cleanup
• Simplify long methods using AI-driven refactoring
• Improve code readability and maintain consistency
• Reduce code duplication with intelligent suggestions

Module 4: Unit Tests & Code Quality

Estimated time: 0.75 hours

• Auto-generate unit tests for service layers
• Create test cases for REST controllers with Copilot
• Implement code comments and documentation using AI

Module 5: Security & Best Practices

Estimated time: 0.75 hours

• Generate security headers and validation logic with Copilot
• Implement common security measures in Spring Boot apps
• Understand AI limitations and validate generated code for compliance

Prerequisites

• Familiarity with Java programming
• Basic understanding of Spring Boot framework
• Experience with REST APIs and JPA/Hibernate

What You'll Be Able to Do After

• Develop Spring Boot applications more efficiently using GitHub Copilot
• Automate generation of models, repositories, and controllers
• Improve code quality and maintainability with AI suggestions
• Accelerate testing and security implementation in Java apps
• Apply context-specific prompts for real-world development tasks