Artificial Intelligence: Principles and Techniques

221

Instructors

Liang, P. (PI)

Sadigh, D. (PI)

Mu, J. (TA)

Karamcheti, S. (TA)

Hughes, J. (TA)

Limonchik, S. (TA)

Kaul, D. (TA)

Becker, N. (TA)

Velu, A. (TA)

Palaparthi, A. (TA)

Gao, I. (TA)

Lin, K. (TA)

Stratta, M. (TA)

Ethayarajh, K. (TA)

Poesia Reis e Silva, G. (TA)

Lowe, S. (TA)

Section Number

Artificial intelligence (AI) has had a huge impact in many areas, including medical diagnosis, speech recognition, robotics, web search, advertising, and scheduling. This course focuses on the foundational concepts that drive these applications. In short, AI is the mathematics of making good decisions given incomplete information (hence the need for probability) and limited computation (hence the need for algorithms). Specific topics include search, constraint satisfaction, game playing,n Markov decision processes, graphical models, machine learning, and logic. Prerequisites: CS 103 or CS 103B/X, CS 106B or CS 106X, CS 109, and CS 161 (algorithms, probability, and object-oriented programming in Python). We highly recommend comfort with these concepts before taking the course, as we will be building on them with little review.

Course Link

http://explorecourses.stanford.edu/search?q=CS221

Grading

Letter or Credit/No Credit

Units

3-4

Academic Career

Graduate

Course Tags

Computational Policy - Electives

Computational Policy Analysis