A living, open-source textbook and curriculum for ML systems engineering — includes the textbook source, TinyTorch reference framework, hands-on labs and hardware kits, plus instructor materials for teaching training, deployment, and system-level trade-offs.
Hands-on coding tutorial series for large language models with slides and runnable notebooks covering fine-tuning, prompting, RLHF, safety, steganography, watermarking, multimodal models, GUI agents, and deployment. Community-maintained, free course materials for students and researchers.
Teaches the foundations and recent advances of large language models through chapter-based PDFs and curated paper lists. Monthly updates keep the syllabus current; bilingual chapter materials and a structured paper list make it suitable for courses and self-study.
