Open Courses
↩ 4x1om.org
University lecture series, newest first
  • Yale: America at 250: A History (Fall 2025)
    Homepage
    https://president.yale.edu/committees-programs/devane-lectures/america-at-250-a-history
    Materials
    Video lectures Slides Notes Problem sets Solutions
    Instructor
    David Blight, Joanne Freeman, Beverly Gage
    Level
    General audience
    Topics
    U.S. political history 1776–present · Race and Reconstruction · Cold War and national security · American identity
    Notes
    One-time-only Yale course for the nation’s 250th anniversary, asking what America is and was meant to be. Three eminent historians, each with a distinct lens. Weekly post-lecture discussions by the professors are also posted to YouTube.
  • MIT 6.8300: Advances in Computer Vision (Spring 2025)
    Homepage
    https://www.scenerepresentations.org/courses/2025/spring/advances-in-cv/
    Materials
    Video lectures Slides Notes Problem sets Solutions
    Instructor
    Vincent Sitzmann
    Known for neural implicit representations (NeRF-adjacent work).
    Level
    Graduate
    Topics
    Neural scene representations · Multi-view geometry · Diffusion models · Contrastive learning · Embodied vision for robotics
    Notes
    Graduate course at the frontier of computer vision, from 3D scene understanding to generative models to robotic perception.
  • Stanford CS221: Artificial Intelligence: Principles and Techniques (Autumn 2025)
    Homepage
    https://stanford-cs221.github.io/autumn2025/
    Materials
    Video lectures Slides Notes Problem sets Solutions
    Instructor
    Percy Liang
    Directs Stanford’s Center for Research on Foundation Models (CRFM); known for benchmarking LLMs.
    Level
    Graduate
    Topics
    Machine learning · Search · Markov decision processes · Bayesian networks · Logic · Language models
    Notes
    Stanford’s flagship AI course, rigorous and broad.
  • MIT MAS.S60: How to AI (Almost) Anything (Spring 2025)
    Homepage
    https://mit-mi.github.io/how2ai-course/spring2025/
    Materials
    Video lectures Slides Notes Problem sets Solutions
    Instructor
    Paul Liang
    Level
    Graduate
    Topics
    Multimodal AI · Foundation models · Medical and sensory data · Audio and video
    Notes
    Graduate seminar on applying modern AI to unconventional data types. Less about any one application, more about the research mindset for tackling new modalities.
4 courses, last updated Mar 21, 2026