The internet's AI syllabus, already bookmarked

What it does This repository is a curated index of external resources for learning machine learning and artificial intelligence. It organizes links to courses, textbooks, YouTube playlists, research blogs, coding problems, and certification guides into an eight-step roadmap that runs from Python basics to job-interview prep. Think of it as a heavily bookmarked syllabus maintained by a stranger who has already done the Googling.

The interesting bit The roadmap actually sequences its links, suggesting you tackle linear algebra before Transformers and MLOps before ArXiv. It also includes a rare “Roles” section that maps a dozen AI/ML job titles—like ML Platform Engineer and Applied Research Scientist—to external descriptions, which is useful in a field that loves vague postings.

Key highlights

• Eight-stage roadmap from Python/core libraries to research papers and interviews
• Curated problem sets ranked Easy, Medium, and Hard, from matrix multiplication up to GANs
• Explicit career-mapping section covering a dozen AI/ML job titles
• Mix of canonical free resources (MIT OCW, fast.ai, 3Blue1Brown) and industry engineering blogs
• Must-read papers list including Attention Is All You Need and DeepSeek R1

Caveats

• This is purely a link aggregator; there is no original content, code, or exercises in the repo itself
• Several linked “free” resources (Coursera, edX, O’Reilly books) sit behind paywalls for full access or certificates
• The README brands itself as a 2025 roadmap, so link-rot and datedness are guaranteed

Verdict Grab this if you are a self-taught beginner who needs structure more than another motivational Twitter thread. Skip it if you are looking for original tutorials, runnable notebooks, or anything beyond a well-organized table of contents.