Web Resources for Artificial Intelligence

Use these resources for a second explanation after reading the local module.

Complete introductory references

• UC Berkeley CS 188 online textbook - agents, search, CSPs, games, probability, logic, and learning.
• Stanford CS 221 course description - the relationship among AI algorithms, probability, and decisions.

Module 1: Agents

• Berkeley CS 188: Agents and search

Module 2: Search, CSPs, and games

• Berkeley CS 188: Search
• Berkeley CS 188: Constraint satisfaction
• Berkeley CS 188: Games

Module 3: Logic and knowledge

• Berkeley CS 188: Logical agents

Module 4: Probability

• Berkeley CS 188: Probability
• Berkeley CS 188: Hidden Markov models

Module 5: Learning and neural networks

• Berkeley CS 188: Machine learning
• Scikit-learn user guide - practical reference for classifiers and neural networks.

Study method

1. Read the local module and trace its worked example.
2. Open a second explanation only when a concept remains unclear.
3. Reproduce the algorithm with a small example on paper.
4. Use code only after the manual trace is understood.