Java Full Stack Placement Program

About this course

Many Java candidates know the syntax but struggle to explain how real backend systems work. This program covers what interviewers commonly test, alongside two full-stack projects with Angular and React frontends and Spring Boot backends. AI-driven development is included throughout.

Prerequisites: For candidates with 0–8 years of experience, including freshers. Ask an expert if you are unsure.

6

Learning units

54

Topics covered

2

Projects

11

Tools

1. 1

   Week 1

   Core Java Essentials for Interviews

   • JVM architecture: heap, stack and garbage collection
   • String pool and immutable classes
   • HashMap vs ConcurrentHashMap internals
   • Java 8: streams, lambdas and functional interfaces
   • Comparable vs Comparator
   • Threads: Runnable, Callable and ExecutorService
   • Synchronization, volatile and atomic classes
   • CompletableFuture basics
   • Deadlock causes and prevention

   By the end of this unit

   • Answer HashMap and JVM questions
   • Write clean Java 8 stream solutions
   • Explain multithreading in interview scenarios
   • Handle common concurrency questions
2. 2

   Week 2

   Spring Boot, Database and Testing

   • IoC, dependency injection and auto-configuration
   • Building REST APIs
   • Validation and global exception handling
   • JPA/Hibernate: entities, relationships and JPQL
   • Pagination, sorting and transactions
   • Optimistic vs pessimistic locking
   • SQL joins and basic query optimization
   • JUnit 5 and Mockito unit testing
   • Swagger / OpenAPI documentation

   By the end of this unit

   • Build the Project 1 backend APIs
   • Explain Spring Boot internals
   • Write testable service-layer code
   • Optimize database queries
3. 3

   Week 3

   Angular Frontend and Project 1 Completion

   • Angular components, modules and routing
   • Reactive and template-driven forms
   • Angular services and HTTP client
   • Connecting Angular to Spring Boot APIs
   • JWT auth flow: login, token storage and guards
   • Role-based UI rendering
   • Docker Compose for frontend and backend
   • Project 1 code review and GitHub push

   By the end of this unit

   • Complete and demo Project 1 end to end
   • Explain the full-stack JWT auth flow
   • Discuss Angular and Spring integration
   • Publish a clean GitHub repository
4. 4

   Week 4

   Microservices and React Frontend

   • Monolith vs microservices trade-offs
   • Service discovery (Eureka) and API Gateway
   • Feign Client inter-service calls
   • Circuit breaker and retry patterns
   • JWT across microservices
   • React hooks, context and Axios
   • Connecting React to microservices through the gateway
   • Redis caching

   By the end of this unit

   • Explain microservices architecture
   • Implement the React frontend for Project 2
   • Discuss circuit breaker and saga patterns
   • Handle service failures gracefully
5. 5

   Week 5

   Kafka, Async Processing and Project 2 Completion

   • Kafka architecture: topics, partitions and offsets
   • Producers and consumers in Spring Boot
   • Consumer groups and parallel processing
   • Retry handling and dead letter queues
   • At-least-once vs exactly-once semantics
   • Async order processing in Project 2
   • Notification service through Kafka events
   • Project 2 code review and GitHub push

   By the end of this unit

   • Explain Kafka internals
   • Implement the event-driven flow in Project 2
   • Handle retry and dead letter scenarios
   • Complete and demo Project 2 end to end
6. 6

   Week 6

   Docker, AWS, Prompt Engineering, AI-Driven Development and Interview Mastery

   • Dockerfiles and multi-stage builds for Spring Boot
   • Docker Compose for frontend, backend and database
   • Pushing images to Docker Hub / ECR
   • Deploying on AWS EC2, with S3 and RDS basics
   • GitHub Actions CI/CD to build and push images on merge
   • Prompt patterns to generate controllers, services and unit tests
   • Zero-shot, few-shot and chain-of-thought prompting
   • Debugging, documentation, code review and refactoring with AI
   • Evaluating AI output: when to trust, verify or rewrite
   • GitHub Copilot, Claude and ChatGPT for backend tasks
   • Mock interviews: architecture, coding and HR rounds
   • Resume and GitHub portfolio review

   By the end of this unit

   • Dockerize and deploy both projects to AWS EC2
   • Build a working CI/CD pipeline with GitHub Actions
   • Write effective prompts for real development tasks
   • Use AI tools to work faster without losing quality

Projects you will build

These are training projects. Please describe them honestly as training work on your resume and in interviews.

Tools and technologies

• Java
• Spring Boot
• Microservices
• Angular
• React
• Docker
• Kafka
• Redis
• AWS
• GitHub Actions
• GitHub Copilot