UC Berkeley · CS 188

Introduction to Artificial Intelligence

人工智能导论

Core artificial-intelligence methods including search, reasoning, planning, and learning.

Subject：Artificial Intelligence

Level：Undergraduate

Suggested stage：Years 2–3 (inferred)

Public-material edition：2026

Language：English

Videos：Not verified

Assignments / solutions：Available / Not verified

Prerequisites

CS 61A →CS 61B →CS 70 →

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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.

36 direct tasks

▶Lectures, video & readingCourse content in the official sequence15

Topic 1: Search Topic 2: Adversarial Search Topic 3: Constraint Satisfaction Topic 4: Markov Decision Processes Topic 5: Reinforcement Learning Topic 6: Probability Review Topic 7: Bayes Nets Topic 8: Hidden Markov Models Topic 9: Decision Networks Topic 10: Machine Learning Topic 11: Regression Topic 12: Classification Topic 13: Neural Networks Topic 14: Language Models Topic 15: Robotics and AI Applications

✓Assignments & practiceOpen the matching problem or assignment page15

◆Labs & projectsCourse projects, labs and milestones6

Project 0: Python Foundations Project 1: Search Project 2: Multi-Agent Search Project 3: Reinforcement Learning Project 4: Ghostbusters Project 5: Machine Learning

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UC Berkeley EECS · verified 2026-07-31

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