Spring Boot Development using AI Coding Assistant
Description
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.
Indicative Duration: 48 training hours
*Duration is adjusted based on the final scope and the target audience.
Scope
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1. Development Environment & Project Setup
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• Spring Boot introduction • Maven • Project setup • AI Practice: AI scaffolds initial Spring Boot app, Generate pom.xml |
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| • Git workflow • Branching • Maven builds • AI Practice: AI suggests project organization, Git commit messages |
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| 2. Application Configuration | • Spring Boot configuration • AI Practice: AI for profiles, properties, logging |
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| 3. Core Spring Framework Concepts | • Dependency injection • Beans • Components • AI Practice: AI suggests service & component structures |
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| 4. Data Persistence layer | • JPA & JDBC integration • AI Practice: AI generates entity classes, repositories, SQL queries |
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5. REST API Development
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• Controllers & REST endpoints • AI Practice: AI generates endpoint templates, suggests validation |
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| • Exception handling & validation • AI Practice: AI generates global exception handlers, validation code |
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| • DTOs • Request/Response mapping • AI Practice: AI generates DTO classes, maps entities |
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| 6. Testing & Quality | • Testing REST APIs • AI Practice: AI generates unit & integration tests |
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7. Security & Observability
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• Security basics (Spring Security) • AI Practice: AI scaffolds auth filters, basic auth & roles |
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| • Observability & monitoring • AI Practice: AI generates logging, metrics suggestions |
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| 8. Capstone Project | • Capstone Project Development • AI Practice: AI scaffolds project, generates tests & documentation |
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Learning Objectives
Upon completion of the course 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
Target Audience
- Roles: Software Engineers, Backend Developers
- Seniority: Junior to Mid-Level Professionals
Prerequisite Knowledge
- Basic understanding of programming concepts
- Experience with Java
Delivery Method
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
