Spring Boot Development using AI Coding Assistant
Certificate of Completion by Code.Hub
This hands-on course teaches participants how to build modern backend applications using Spring Boot while leveraging AI as a development accelerator. Throughout the program, AI tools are used to scaffold projects, suggest architectural patterns, generate tests, and support refactoring. The focus is on strengthening backend engineering skills while learning how to critically evaluate and effectively collaborate with AI-assisted development tools.
By the end of this module, participants will be able to:
- Develop structured RESTful applications using Spring Boot best practices
- Use AI tools to scaffold, refactor, and document backend services
- Critically evaluate AI-generated code for correctness, security, and design quality
- Implement data persistence and secure API endpoints in a structured backend application
- Apply AI-assisted testing and documentation techniques within a production-style workflow
Development Environment & Project Setup
Spring Boot introduction
Maven
Project setup
AI Practice: AI scaffolds initial Spring Boot app, Generate pom.xml
Git workflow
Branching
Maven builds
AI Practice: AI suggests project organization, Git commit messages
Application Configuration
Spring Boot configuration
AI Practice: AI for profiles, properties, logging
Core Spring Framework Concepts
Dependency injection
Beans
Components
AI Practice: AI suggests service & component structures
Data Persistence layer
JPA & JDBC integration
AI Practice: AI generates entity classes, repositories, SQL queries
REST API Development
Controllers & REST endpoints
AI Practice: AI generates endpoint templates, suggests validation
Exception handling & validation
AI Practice: AI generates global exception handlers, validation code
DTOs
Request/Response mapping
AI Practice: AI generates DTO classes, maps entities
Testing & Quality
Testing REST APIs
AI Practice: AI generates unit & integration tests
Security & Observability
Security basics (Spring Security)
AI Practice: AI scaffolds auth filters, basic auth & roles
Observability & monitoring
AI Practice: AI generates logging, metrics suggestions
Capstone Project
Capstone Project Development
AI Practice: AI scaffolds project, generates tests & documentation
- Roles: Software Engineers, Backend Developers
- Seniority: Junior to Mid-Level Professionals
- Basic understanding of programming concepts
- Experience with Java
Sessions can be delivered via the following formats:
- Live Online – Interactive virtual sessions via video conferencing
- On-Site – At your organization’s premises
- In-Person – At Code.Hub’s training center
- Hybrid – A combination of online and in-person sessions
Interested for
