Foundation Building
Content:
- Course introduction and career path planning
- Quick start with Java (SpringBoot) vs Python (FastAPI)
- Basic operations with Git / GitHub / GitLab
- IDE setup (IntelliJ / VS Code)
- RESTful API vs gRPC: Basic concepts and differences
- Mini project exercise: Build a CRUD API for employee management
Lab:
- Create a basic API service using SpringBoot or FastAPI (with create, read, update, delete)
- Deploy locally using Docker
Cloud Computing & Docker
Content:
- Introduction to AWS/GCP cloud services (IAM / EC2 / S3 / Lambda / SQS)
- Use AWS CLI to upload files and send SQS messages
- Docker fundamentals (build, run, compose)
- Dockerize your Flask or SpringBoot project
- Introduction to CI/CD (GitHub Actions / Jenkins basics)
Lab:
- Build a Docker image for last week's project
- Deploy the image to a cloud server (or local Kubernetes environment)
Kubernetes & Project Development
Content:
- Core Kubernetes concepts (pod, service, ingress)
- Install services like MySQL/Postgres/Weaviate using Helm Charts
- Deploy a full application on K8s (including VectorDB)
- System design discussion (scalability, fault tolerance, high availability)
- Guide to start final project: RAG (Retrieval-Augmented Generation) chat system
Lab:
- Read the base framework of the RAG project, choose a tech stack (Java or Python)
- Begin building document upload + vectorization + query API
RAG Implementation & Interview Prep
Content:
- Basic architecture of Retrieval-Augmented Generation
- Introduction to vector databases: Weaviate, Chroma, FAISS
- Prompt template design and context chunking strategies
- Using OpenAI/LLMs for question-answering
- Interview techniques (system design, project presentation, Leetcode strategies)
- Final project presentation practice
Lab:
- Complete project deployment and documentation
- Prepare a 10-minute project presentation (PPT + Demo)