- Build real-world RAG (Retrieval-Augmented Generation) AI applications from scratch
- Understand how Agentic AI systems work and how to design them
- Use Local LLMs (LLaMA via Ollama) — no API cost required
- Create intelligent AI assistants that can read, understand, and answer from documents
- Work with LangChain, FAISS, and embeddings for building scalable AI systems
- Load and process PDF, TXT, and custom data sources for AI applications
- Design and implement vector databases for efficient information retrieval
- Build a complete RAG pipeline (Retriever + Generator) step-by-step
- Develop ChatGPT-like web apps using Streamlit
- Create multi-tool Agentic AI systems with reasoning capabilities
- Implement prompt engineering techniques for better AI responses
- Learn how to structure production-ready AI projects
- Build industry use cases like Resume Analyzer, Chatbot, Research Assistant
- Debug and optimize AI systems for better performance and accuracy
- Deploy and run AI applications locally for real-world usage
- Gain practical skills to start a career in Generative AI & AI Engineering
- Build a strong portfolio with real-world AI projects
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