Java Engineer Developer: Mastering Core Programming, Backend Systems & the Java Ecosystem for Scalable Cloud Applications
Course Overview: This program provides a comprehensive path from beginner to advanced level in full-stack development and cloud infrastructure. Key topics include 1) Spring Boot & Micronaut development 2) Kafka message-driven systems 3) Cloud deployment with Docker, Kubernetes, and AWS 4) CI/CD automation with GitHub Actions 5) Infrastructure-as-code with Helm, Terraform & ArgoCD 6) Monitoring and tracing with Datadog 7) Advanced security, database design, and system architecture. By the end of the program, you will have the practical expertise needed to create modern microservices applications, automate deployments, and monitor them in production environments.
Course Description
Are you ready to become a skilled Java Backend Engineer equipped with the tools and expertise needed to thrive in modern software development? Over the span of 6 months, this immersive program will take you from foundational Java skills to advanced backend engineering practices, combining hands-on projects with real-world tools and cloud-native technologies. You'll begin by mastering core Java programming and building powerful, production-ready RESTful APIs using Spring Boot. You'll explore message-driven architectures with Kafka, and gain proficiency in Git version control operations like fetch, pull, push, merge, and rebasing across platforms such as GitHub and GitLab. As you dive deeper, you'll learn to design scalable CI/CD pipelines for automated testing and deployments using tools like GitHub Actions and GitLab CI. The course covers modern API development patterns including REST, GraphQL, and API documentation with OpenAPI. You'll learn how to integrate SQL databases (with DDL, DML, and optimization techniques) as well as NoSQL and cloud databases like MongoDB and DynamoDB. With Docker and Docker Compose, you'll containerize your applications, then deploy and manage them at scale using Kubernetes and Helm Charts. Additionally, you’ll develop cloud-native applications on AWS, leveraging services such as EC2, Lambda, API Gateway, SQS, and SNS. You'll also be introduced to Infrastructure-as-Code using Terraform, ensuring reproducibility and automation in your infrastructure management. Security best practices, including secrets management, HTTPS, and OWASP principles, will be embedded throughout your journey. Frontend integration isn't left behind — you’ll gain basic exposure to building responsive UIs using React and Next.js to better understand full-stack development workflows. You’ll also build the skills to conduct effective pull request (PR) reviews, write clean and maintainable code, and work in Agile teams. By the end of this course, you will have built a portfolio of projects demonstrating real-world proficiency in backend engineering, cloud deployment, automation, and scalable system design. Whether you're looking to break into the tech industry or level up your existing skills, this course offers a career-transforming path to becoming a confident, job-ready Java Backend Engineer.
Fee Breakdown
📆 Then, pay £714.00/month for 5 months.
Choose Your Ideal Start Date!
Key Technology Tags
Features
Seats Available:50 seats
Instructed In:English
Installment Allowed:Yes
Instructor:Edwin Nwofor
Delivery Mode:Online
Next Starting:01/11/2025
Duration:6 months
Institution:CEN IDEA LTD
Before You Begin – What You Need to Know!
Make sure you're ready for this course by reviewing these key prerequisites.
- Basic understanding of Java syntax, object-oriented programming concepts (classes, inheritance, polymorphism).
- Ability to write and debug simple Java programs independently.
- Familiarity with Git, GitHub, and collaborative version control workflows (e.g., branching, pull requests).
- Understanding of basic terminal/command line operations (navigating directories, running scripts).
- Problem-solving mindset and basic algorithmic thinking (e.g., breaking down problems into steps).
What You'll Gain from This Course
- Enable students to build microservices applications using Spring Boot and Micronaut.
- Introduce message-driven architectures with Kafka and event-driven systems.
- Provide hands-on experience in containerization with Docker, Kubernetes, and cloud platforms (AWS).
- Equip students with the skills to automate testing, deployment, and infrastructure management using Terraform and Helm.
- Teach monitoring and tracing in production using Datadog for logs, metrics, and performance optimization.
- Cover advanced security practices, database design, and architectural patterns for scalable systems.
Course Syllabus
- Introduction to Java: History, Philosophy, Java Platform Overview
- Setting Up Development Environment: JDK, IntelliJ IDEA / Eclipse
- Basic Syntax: Variables, Data Types, Type Casting
- Operators and Expressions: Arithmetic, Logical, Relational Operators
- Control Flow Statements: if-else, switch-case, while, for, do-while loops
- Introduction to Debugging in IDE
- Methods: Defining Methods, Parameters, Return Types, Method Overloading
- Classes and Objects: Creating Classes, Instantiating Objects, Constructors
- Basic Inheritance: Understanding 'extends', Method Overriding
- Access Modifiers: public, private, protected, default
- Exception Handling: try-catch-finally blocks, Checked vs Unchecked Exceptions
- Practical Hands-on: Build a Simple Java Console App (Mini Project)
- Java 17+ Features: Records, Sealed Classes, Pattern Matching
- OOP and Functional Programming: Streams, Lambdas
- Concurrency: Threads, CompletableFuture, ExecutorService
- Design Patterns: Factory, Observer, Circuit Breaker
- JVM Internals: Memory Management, Garbage Collection
- Maven & Gradle: Dependency Management, Multi-Module Projects
- JUnit 5 & Mockito for Unit and Integration Testing
- Testcontainers for Real DB Testing in Containers
- Why Generics? (type safety, DRY code)
- Basic syntax of Generic classes and methods (<T>)
- Generic Types vs Raw Types
- Working with Generic Collections (List, Set, Map)
- Single vs Multiple Type Parameters (<K, V>)
- Bounded type parameters (<T extends Number>)
- Unbounded wildcards (<?>)
- Upper bounded (<? extends T>) and lower bounded (<? super T>) wildcards
- PECS Rule: Producer Extends, Consumer Super
- Hands-on: Create GenericBox<T>, Pair<K,V>, and GenericStack<T>
- Recursive bounds (<T extends Comparable<T>>)
- Multiple bounds (<T extends Number & Comparable<T>>)
- Limitations due to Type Erasure (cannot instantiate T)
- Best Practices with Wildcards
- Avoiding raw types and unchecked warnings
- Real-world examples from Spring Framework and Collections API
- Mini Project: Generic Repository Pattern
- Mini Project: Sorting a generic list
- Mini Project: Capturing wildcards in methods
- Review + Solve small coding exercises
- Arrays and Strings (basics, manipulation, searching)
- Linked Lists (singly, doubly, common operations)
- Stacks and Queues (using arrays and linked lists)
- Priority Queues and Heaps (intro to heap properties)
- HashMaps and HashSets (internal working and usage)
- Tree Structures Overview (Binary Trees, traversal basics)
- Hands-on Practice: Reverse a Linked List, Implement Stack using Queues, Basic tree traversal
- Spring Boot: Auto-Configuration, Actuator
- Spring Data JPA: Hibernate, QueryDSL
- Spring Security: OAuth2, JWT, OpenID Connect
- Spring Cloud: Config Server, Gateway, Resilience4j
- Spring WebFlux: Reactive Programming
- REST APIs: HATEOAS, Versioning, Pagination
- GraphQL: Schema Design, Apollo Federation
- gRPC: Protocol Buffers & Streaming APIs
- OpenAPI/Swagger for API Documentation
- PostgreSQL/MySQL: Indexing, Transactions, Stored Procedures
- Liquibase/Flyway: Schema Migration
- MongoDB: Aggregation Pipeline
- Redis: Caching & Pub/Sub
- DynamoDB & Elasticsearch Integration
- Kafka: Partitions, Topics, Consumer Groups
- RabbitMQ: Queues, DLQs, Routing Patterns
- AWS SQS/SNS & Fanout Patterns
- Event Sourcing & CQRS with Axon Framework
- Saga Pattern for Distributed Transactions
- Docker: Images, Volumes, Networking
- Docker Compose: Multi-Container Setup
- Kubernetes: Pods, Deployments, Services
- Helm: Charts, Templates
- GitOps with ArgoCD/Flux
- AWS: EC2, Lambda, RDS, S3, IAM
- Azure/GCP Overview: AKS, Functions, BigQuery
- Terraform: Modules, State Management
- AWS CDK: Java SDK for Infrastructure-as-Code
- GitHub Actions, Jenkins, GitLab CI for Pipelines
- SonarQube for Code Quality
- Artifactory/Nexus for Artifact Management
- Git Strategies: Rebase, Cherry-Pick, PR Reviews
- OWASP Top 10, HTTPS, Vault for Secrets
- Prometheus + Grafana for Metrics
- ELK Stack: Centralized Logging
- OpenTelemetry + Jaeger for Tracing
- React/Next.js for API Integration
- HTML/CSS/JS for API Contract Understanding
- Microservices & Monolith-to-Microservices Migration
- Hexagonal Architecture & DDD Principles
- Caching, Load Balancing, CDN Strategies
- Agile Workflows, Sprint Planning, Code Reviews
- System Design Interviews & Documentation Practices
- Build REST/GraphQL API with Spring Boot + K8s Deployment
- Create Event-Driven Microservice with Kafka & Docker
- Deploy Serverless Java App on AWS Lambda
- Books: Clean Code, Designing Data-Intensive Applications
- Practice: LeetCode, Excalidraw, System Design Tools
No Reviews on this room