Intro to AI
- MIT 6.034: AI [Fall 2010]
- Berkeley CS188: Intro to AI [Fall 2022] [Fall 2021] [Fall 2020]
- Harvard CS50: Intro to AI with Python [edX]
- Stanford CS221: AI: Principles and Techniques [Autumn 2019] [Autumn 2021]
Perspectives on AI by Prof. Song-Chun Zhu
- 正本清源 | 初探计算机视觉的三个源头、兼谈人工智能 (2016年11月)
- 学术人生 | 文章千古事，得失寸心知 (2017年1月)
- 正本清源 : 浅谈人工智能：现状、任务、构架与统一 (2017年11月)
Intro to ML
- Prof. Ying Nian Wu at UCLA has organized some fantastic machine learning course material and videos for undergrads. You can view on his homepage. See also A Note on Machine Learning Methods.
- 西瓜书
- Stanford CS229: ML [Autumn 2018]
- Stanford CS230: Deep Learning [Autumn 2018]
- Intro to RL with David Silver
- Deep RL by OpenAI Spinning Up
Advanced ML
- Pattern Recognition and Machine Learning
- The Elements of Statistical Learning
- Machine Learning: a Probabilistic Perspective
- Probabilistic Machine Learning: An Introduction
- Probabilistic Machine Learning: Advanced Topics
- Stanford CS224W: ML with Graphs [Fall 2021]
- Stanford CS234: RL [Winter 2019]
- Stanford CS330: Deep Multi-Task and Meta Learning [Autumn 2019] [Autumn 2020] [Autumn 2021]
- Neurosymbolic Reading Group
Intro to CV
- Siyuan Huang and I are offering a CV course at PKU
- Intro to Computer Vision by Noah Snavely
- Computer Vision by Justin Johnson and David Fouhey
- Deep Learning for Computer Vision by Justin Johnson
- Advances in Computer Vision by Bill Freeman
- MATLAB Functions for Multiple View Geometry by Andrew Zisserman
Advanced CV
- Stanford CS231n: CNN for Visual Recognition [Spring 2017]
- Stanford CS25: Transformers United [Autumn 2021]
- Computer Vision: Statistical Models for Marr’s Paradigm
- Computer Vision: Stochastic Grammars for Parsing Objects, Scenes, and Events
- Cognitive Models for Visual Commonsense Reasoning
- Monte Carlo Methods
Intro to NLP
Advanced NLP
- Stanford CS224N: NLP with Deep Learning [Winter 2019] [Winter 2021]
- Stanford CS224U: NLU [Spring 2019] [Spring 2021]
- NYU Computational Linguistics and Cognitive Science [Spring 2023]
Intro to Psychology
- 改变心理学的40项研究
- 对伪心理学说不
- 心理学与生活
- 津巴多普通心理学
- 认知心理学
- 感觉与知觉
- MIT 9.00SC: Intro to Psychology [Fall 2004] [Fall 2011]
- MIT 9.13: The Human Brain [Spring 2019]
Intro to CoRe
- I’m offering a cognitive reasoning course at PKU
- In AI, is bigger always better?
- What Babies Know, Volume 1, Core Knowledge and Composition
- The Origin of Concepts
- Origins of Human Communication
- Computational cognitive modeling
Advanced CoRe
- MIT RES.9-003: Brains, Minds And Machines Summer Course [Summer 2015]
- MIT 6.868J: The Society of Mind [Fall 2011]
- Causal Cognition by Tobi Gerstenberg
- Intro to Causal Inference by Brady Neal
- Language and Thought by Noah D. Goodman
- Probabilistic Models of Cognition
- Communication, Intentionality, and the Origins of Language by Michael C. Frank and Fei Xu
- A minimalist guide to program synthesis by Evan Pu
- Nancy’s Brain Talks by Nancy Kanwisher
- Categories and Concepts by Brenden Lake
- Github Awesome AGI and CoCoSci maintained by Yu-Zhe Shi
Intro to Robotics
- Isaac Sim
- ROS
- Intro to Robotics by Marc Toussaint
- Stanford CS223A: Intro to Robotics
- MIT 6.4210/6.4212: Robotic Manipulation [Fall 2022]
- Northwestern Modern Robotics
- 学用Isaac Sim快速入门机器人仿真开发
Advanced Robotics
- MIT 6.832: Underactuated Robotics [Spring 2019] [Spring 2022]
- MIT 16.412J: Cognitive Robotics [Spring 2016]