Stanford University · CS221

Artificial Intelligence: Principles and Techniques

人工智能：原理与技术

Search, decision theory, graphical models, machine learning, logic, and applications to language, vision, robotics, and games.

Subject：Artificial Intelligence

Level：Advanced Undergraduate

Suggested stage：Years 3–4 (inferred)

Public-material edition：2026

Language：English

Videos：Not available

Assignments / solutions：Available / Not available

Prerequisites

Data structures →Probability →Linear algebra →Programming →

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All official course content

Lectures, video, assignments and exams are separated so you do not have to hunt through the course homepage.

30 direct tasks

▶Lectures, video & readingCourse content in the official sequence12

Topic 1: Machine Learning Topic 2: Search Topic 3: Markov Decision Processes Topic 4: Game Playing Topic 5: Constraint Satisfaction Topic 6: Bayesian Networks Topic 7: Logic Topic 8: Deep Learning Topic 9: Natural Language Processing Topic 10: Computer Vision Topic 11: Robotics Topic 12: AI Ethics

✓Assignments & practiceOpen the matching problem or assignment page12

◆Labs & projectsCourse projects, labs and milestones6

Foundations Sentiment Classification Text Reconstruction Blackjack Pac-Man Final AI Project

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Homework and programming assignmentsStanford Computer Science ↗

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Stanford Computer Science · verified 2026-08-04

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