A 2025–2026 guide to AI and CS course access at Stanford, CMU, MIT, UC Berkeley, Harvard, and universities in Taiwan, distinguishing complete self-study courses from public syllabi, partial materials, and historical videos.
This map audits AI and CS courses at Stanford, CMU, MIT, UC Berkeley, Harvard, and National Taiwan University (NTU) in 2025–2026 using four access labels: A0 for a visible catalog entry, A1 for a public syllabus, A2 for partial materials, and A3 for a self-study-ready package. A course site or YouTube playlist can exist without giving outsiders access to the current videos, assignments, or starter code.
Stanford CS rests on CS103, CS107, CS109, CS111, and CS161; CS221 names three of those plus CS106B as preparation. This guide combines official prerequisites with an explicitly editorial reading order and marks public-material and offering risks.
CMU's current BSAI now runs through 07-280 and 07-380 before branching into an NLP/vision core and four AI clusters. 07-380 debuted in Fall 2026, and the same semester launched a graduate-level 11-768 AI Agents course. The residual Spring 2026 materials for 07-280 and the complete 10-301/601 site already support self-study; retired 15-281 remains a useful legacy route.
MIT has offered Course 6-4, a formal BS in Artificial Intelligence and Decision Making, since 2022. For an outside learner, however, the current degree requirements, the 2025–2026 course sites, and the best OCW editions rarely line up. A workable route follows 6-4's programming, algorithms, linear algebra, and probability foundation, then selects among 6.S191, 6.3900, 6.4110, 6.7960, vision, and robotics according to what is actually public.
Berkeley has no standalone undergraduate AI degree. A workable path builds on the CS BA or EECS BS foundation, enters through either CS188's broad AI curriculum or CS189's mathematical machine learning curriculum, then branches into deep learning, NLP, vision, or reinforcement learning. Many 2025–2026 courses are A3, but the newest class, the newest stable URL, and the best self-study edition are not always the same.
CS50 AI is Harvard's most complete public entry point, but the Summer 2026 course still uses 2020 recordings and assignment assets while the rolling OCW projects have moved to other editions. CS181 Spring 2026 exposes current homework and notes without current recordings; CS182 Fall 2026 has not yet completed an offering.
National Taiwan University spreads its AI/ML courses across Electrical Engineering and Computer Science, and an official 'Machine Learning and AI' specialization stacks them into four levels. Hung-yi Lee's courses are the most open: ML 2026 Spring and Intro to GenAI and ML 2025 Fall publish slides, recordings, homework PDFs, and Colab notebooks, with only grading held back. Hsuan-Tien Lin's lectures are fully recorded and his Fall 2024 HW0–HW7 remain on the course page; Yun-Nung Chen's lectures are fully recorded, but most homework is public only as walkthrough videos; and since August 2025 Coursera only lets free learners watch the first module.
Most public AI courses in Taiwan outside NTU come from TAICA, an alliance set up by the Ministry of Education. Each semester's course list says where every flagship course streams, and courses that stream on YouTube are usually watchable by anyone. Two courses are complete enough to self-study: Hung-Yu Kao's Natural Language Processing at NTHU (Fall 2025) and Yen-Lung Tsai's Generative AI at NCCU (Spring 2025), both A3. Wei-Ta Chu's Introduction to AI at NCKU, Ping-Hsuan Han's Human-AI Interaction at NTUT, and Min-Chun Hu's Robotic Navigation and Exploration at NTHU have full recordings but keep assignments on NTU COOL, so they rate A2. NYCU's TAICA courses are taught in English; the Deep Learning recordings are not publicly listed and Physical AI has just started, so neither made the main table.