🏛️ Foundational AI & Deep Learning Lecture Notes

Microsoft AI for Beginners (microsoft/AI-For-Beginners): A massive 12-week, 24-lesson comprehensive academic curriculum. It features exhaustive lecture notes, mindmaps, and code labs spanning from Symbolic AI (GOFAI) to modern Neural Networks using TensorFlow and PyTorch.
👉 Microsoft AI-For-Beginners GitHub Repository [1, 2]The LLM Course by Maxime Labonne (mlabonne/llm-course): One of the most popular, structured academic curricula tracking the progression from simple Transformer concepts to advanced Large Language Model engineering. It covers key-value attention mechanics, sampling strategies, and tokenization theory.
👉 mlabonne/llm-course GitHub Repository [1, 2, 3, 4]Stanford CS324: Large Language Models (Curriculum Guide): While the official Stanford text sits on their domain, open repositories like the AI System Design Guide provide curated summaries and study links to this landmark course. It covers scaling laws, model alignment (RLHF), and token budget management.
👉 AI System Design Guide / CS324 Curated Resource [1]