Stanford Root

Schedule

Stanford Root

Schedule

CS 221

Artificial Intelligence: Principles and Techniques

UNITS:3-4
GRADING:Letter or Credit/No Credit
LEVEL:Graduate
GER:—

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.

Syllabus for selected term:
View Autumn 2026 Syllabus

Sections

2 Terms
Lecture 1Open
ID: 1903
0 / 500 enrolled
DAYS:Tuesday, Thursday
TIME:3 PM – 4:20 PM
LOCATION:Hewlett Teaching Center 200
INSTRUCTOR:
Liang, Percy
units

CS 221: Artificial Intelligence: Principles and Techniques

3-4 units · Letter or Credit/No Credit

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.

Offered in Autumn 2026, Spring 2027 at Stanford University.

Autumn 2026 sections

  • Lecture — Tuesday Thursday 3:00 PM – 4:20 PM — Hewlett Teaching Center 200 — Liang, Percy (Graduate)

Spring 2027 sections

  • Lecture — Monday Wednesday 10:30 AM – 12:20 PM — Charikar, Moses, Weng, Shiny, Badlani, Adi, Chudnovsky, Jessica, Yan, Sydney, Shkirko, Illia, Sinha, Isha, Zhang, Yibo, Sun, Livia, Ge, Chenhao (Graduate)

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  • CS 218: Information Integrity
  • CS 220: Researching, Presenting and Publishing Work in AI & Education (EDUC 481)
  • CS 221M: Mechanistic Interpretability
  • CS 223A: Introduction to Robotics (ME 320)
  • CS 224G: Apps With LLMs Inside
  • CS 224N: Natural Language Processing with Deep Learning (LINGUIST 284, SYMSYS 195N)
  • CS 224R: Deep Reinforcement Learning
  • CS 224U: Natural Language Understanding (LINGUIST 188, LINGUIST 288, SYMSYS 195U)

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