SkalskiP/courses

The collection organizes resources in a structured table with filterable metadata including topic, format (YouTube, website, book, GitHub repo), difficulty level, release year, and pricing—enabling targeted discovery across generative AI, deep learning, NLP, computer vision, reinforcement learning, and foundational mathematics. Content spans multiple institutions (MIT, Stanford, CMU, DeepMind) and platforms, with an automated table generation system for maintainability. Community contributions are actively solicited through pull requests, particularly for mathematics foundations like statistics and linear algebra that complement practical AI coursework.

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