Topics
Foundations
Core concepts behind LLMs: Transformers, Tokenization, Embeddings and more
7 lessonsLocal Models
Deploy and run open-source models locally: Ollama, llama.cpp, quantization
6 lessonsPrompt Engineering
Effective prompting techniques: prompt design, few-shot, chain of thought
6 lessonsRAG
Retrieval-Augmented Generation: vector databases, embedding search, knowledge bases
6 lessonsFine-tuning
Model fine-tuning: LoRA, dataset preparation, training pipelines and evaluation
6 lessonsAgents
AI agents: tool use, ReAct pattern, multi-step reasoning and autonomous execution
6 lessons