Course guide
A route into our Chinese-language course reviews and comparisons.
Our short answer
For a structured free path in Chinese, Datawhale’s tutorials are the most practical entry. Li Hongyi’s recorded lectures are the strongest theory option. PKU’s AI principles course suits learners who want a university-framed overview. All three are covered in our Chinese-language reviews.
Datawhale offers the most practical structured free entry in Chinese in this shortlist. Li Hongyi’s recorded lectures provide a stronger theory route, while PKU’s AI principles course offers a university-framed overview. Choose one spine and use the others to fill gaps instead of trying to finish all three at once.
Choose Datawhale when guided exercises and community-organized tutorials matter most. Li Hongyi’s lectures are the stronger theory choice, and PKU provides a broader academic overview. All three are free options covered in Chinese-language reviews, so time and learning format are the real constraints.
Use the full reviews below to compare fit, workload, and current course details before you choose.
| Course | Rating | Best for | Time | Price |
|---|---|---|---|---|
| Hung-yi Lee's Machine Learning / Generative AI Lectures | 4.5/5 | Chinese-speaking learners who want the friendliest on-ramp to deep learning and modern LLM concepts, and anyone who prefers 'understand the principles' over 'memorize the tooling' | One semester of material; roughly 30–50 hours to watch everything, significantly more with assignments | Completely free; grading and credits are reserved for enrolled NTU students |
| Principles of Artificial Intelligence (Peking University) | 4.0/5 | Chinese-speaking CS undergrads and self-learners who want a rigorous classical-AI foundation (search, reasoning, planning, learning), and anyone who wants bilingual Chinese-English AI terminology | 12 weeks, 12 lectures; officially 3–5 hours per week, roughly 40–60 hours total | Free to watch and take quizzes; the verified certificate requires a fee — the price isn't visible without login, so check the course page at enrollment |
| Datawhale Open-Source AI Tutorials (Pumpkin Book, llm-universe, self-llm, happy-llm) | 4.5/5 | Chinese-reading students and career changers who want to learn AI/LLMs at zero cost — especially people who want to build an LLM from scratch (happy-llm) or survive the Watermelon Book's math (Pumpkin Book) | No unified hours: llm-universe part one takes a few hours; happy-llm has 8 chapters with tens of hours of reproduction work; Pumpkin Book is a companion you consult alongside the textbook; self-llm is pick-what-you-need | All tutorial content is completely free and open source; the Pumpkin Book has a paid print edition (check retailer pricing), and self-llm practice requires renting GPU compute at your own cost |
National Taiwan University (NTU) — Prof. Hung-yi Lee
Best for: Chinese-speaking learners who want the friendliest on-ramp to deep learning and modern LLM concepts, and anyone who prefers 'understand the principles' over 'memorize the tooling'
Peking University — Prof. Wang Wenmin (Chinese University MOOC / XuetangX)
Best for: Chinese-speaking CS undergrads and self-learners who want a rigorous classical-AI foundation (search, reasoning, planning, learning), and anyone who wants bilingual Chinese-English AI terminology
Datawhale open-source learning community
Best for: Chinese-reading students and career changers who want to learn AI/LLMs at zero cost — especially people who want to build an LLM from scratch (happy-llm) or survive the Watermelon Book's math (Pumpkin Book)
Reviews on this page verified 2026-08-22; each links its own dated sources.