Theory and practice of Large Language Models including the underlying architectures (transformers, attention mechanisms), training methodologies (pretraining, fine-tuning, instruction-tuning, RLHF), prompt engineering, LLM-based agents, multimodal LLMs, evaluation metrics, deployment, and the ethical and societal challenges of LLMs.