Gain a deep understanding of language models like GPT and LLAMA, exploring key concepts such as attention mechanisms, transformers, and text embeddings. Learn to build LLM-powered applications with frameworks like Hugging Face and LangChain, and develop your own retrieval-augmented generation (RAG) tools.

Master advanced techniques like prompt engineering, X-shot learning, and chain-of-thought reasoning. Dive into the core principles of RAG, including retrieval methods, vector databases, and chunking. Finally, apply your knowledge by building LLM-driven applications with RAG, agents, and various memory strategies.