Become proficient in large language models: prompting, RAG, fine-tuning, agents, and production LLM systems.
Master Python fundamentals and essential libraries for ML including NumPy, pandas, and scikit-learn.
Advanced prompting techniques: chain-of-thought, few-shot, constitutional AI, and systematic evaluation.
Master LLM architecture, prompt engineering, RAG, fine-tuning, agents, and production deployment.
Vector databases, embeddings, chunking strategies, hybrid search, and production RAG systems.
Understand attention mechanisms, build transformers from scratch, and explore BERT, GPT, and beyond.