BACKEND ENGINEERINGDuration: 6 months
Spring Boot, microservices, Kafka & Spring AI
Learn to design, develop, test and deploy production-style backend applications. Build REST
APIs, connect applications to databases and understand event-driven systems used in modern
organisations.
- Spring Framework fundamentals: IoC, dependency injection, beans and application
context
- Spring Boot architecture, auto-configuration, starters and project setup
- Configuration management, profiles, properties and environment-specific settings
- Spring MVC, REST controllers, request mapping and API design
- DTOs, request validation, exception handling and global exception handlers
- Spring Data JPA, Hibernate, entity relationships, repositories and query methods
- Database transactions, transaction propagation and isolation basics
- Spring Security, authentication, authorization, JWT and OAuth2 fundamentals
- Unit and integration testing with JUnit, Mockito and Spring Boot Test
- Logging, Spring Boot Actuator, monitoring and application health checks
- Caching, asynchronous processing, scheduling and API documentation with
OpenAPI/Swagger
- Microservices architecture, service discovery, API gateway and inter-service
communication
- Apache Kafka: brokers, topics, partitions, producers, consumers and consumer groups
- Kafka offsets, delivery semantics, retries, error handling and dead-letter topics
- Event-driven architecture and integrating Kafka with Spring Boot applications
- Spring AI fundamentals, architecture and integration with Spring Boot applications
- Working with LLM providers such as OpenAI and other model integrations
- Prompt engineering, prompt templates and structured AI responses
- ChatClient API, chat models and conversation management
- Embedding models, vector databases and semantic search
- Retrieval-Augmented Generation (RAG) and building document-based AI applications
- Function calling and tool calling to connect AI models with external services
- AI-powered REST APIs and intelligent backend application development
- Responsible AI basics, error handling, observability and evaluation of AI responses
- Build an end-to-end Spring AI project integrating an LLM, vector store and backend
services
- Build end-to-end backend projects with database integration and deployment
fundamentals