AIMA
Artificial Intelligence: A Modern Approach
Lectures
Reveal.js slides with TTS narration and captions. Click to open.
- Lecture 0: GitHub Classroom Assignments (Getting Started)
- Lecture 1: Introduction (Artificial Intelligence)
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- Lecture 2: Intelligent Agents (Artificial Intelligence)
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- Lecture 3: Solving Problems by Searching (Problem-Solving)
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- Lecture 4: Search in Complex Environments (Problem-Solving)
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- Lecture 5: Adversarial Search and Games (Problem-Solving)
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- Lecture 6: Constraint Satisfaction Problems (Problem-Solving)
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- Lecture 7: Logical Agents (Knowledge, Reasoning, and Planning)
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- Lecture 8: First-Order Logic (Knowledge, Reasoning, and Planning)
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- Lecture 9: Inference in First-Order Logic (Knowledge, Reasoning, and Planning)
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- Lecture 10: Knowledge Representation (Knowledge, Reasoning, and Planning)
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- Lecture 11: Automated Planning (Knowledge, Reasoning, and Planning)
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- Lecture 12: Quantifying Uncertainty (Uncertain Knowledge and Reasoning)
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- Lecture 13: Probabilistic Reasoning (Uncertain Knowledge and Reasoning)
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- Lecture 14: Probabilistic Reasoning over Time (Uncertain Knowledge and Reasoning)
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- Lecture 15: Probabilistic Programming (Uncertain Knowledge and Reasoning)
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- Lecture 16: Making Simple Decisions (Uncertain Knowledge and Reasoning)
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- Lecture 17: Making Complex Decisions (Uncertain Knowledge and Reasoning)
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- Lecture 18: Multiagent Decision Making (Uncertain Knowledge and Reasoning)
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- Lecture 19: Learning from Examples (Machine Learning)
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- Lecture 20: Learning Probabilistic Models (Machine Learning)
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- Lecture 21: Deep Learning (Machine Learning)
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- Lecture 22: Reinforcement Learning (Machine Learning)
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- Lecture 23: Natural Language Processing (Communicating, Perceiving, and Acting)
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- Lecture 24: Deep Learning for Natural Language Processing (Communicating, Perceiving, and Acting)
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- Lecture 25: Computer Vision (Communicating, Perceiving, and Acting)
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- Lecture 26: Robotics (Communicating, Perceiving, and Acting)
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- Lecture 27: Philosophy, Ethics, and Safety of AI (Conclusions)
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- Lecture 28: The Future of AI (Conclusions)
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Assignments
GitHub Classroom assignments — one per lecture. Accept to get your own repo with exercises and AI-assisted tools.
Open GitHub Classroom →
Accept the assignment for each lecture to get your repo. Use Cursor or Codespaces with the curriculum MCP tools.
- Lecture 1: Introduction (Artificial Intelligence)
- Lecture 2: Intelligent Agents (Artificial Intelligence)
- Lecture 3: Solving Problems by Searching (Problem-Solving)
- Lecture 4: Search in Complex Environments (Problem-Solving)
- Lecture 5: Adversarial Search and Games (Problem-Solving)
- Lecture 6: Constraint Satisfaction Problems (Problem-Solving)
- Lecture 7: Logical Agents (Knowledge, Reasoning, and Planning)
- Lecture 8: First-Order Logic (Knowledge, Reasoning, and Planning)
- Lecture 9: Inference in First-Order Logic (Knowledge, Reasoning, and Planning)
- Lecture 10: Knowledge Representation (Knowledge, Reasoning, and Planning)
- Lecture 11: Automated Planning (Knowledge, Reasoning, and Planning)
- Lecture 12: Quantifying Uncertainty (Uncertain Knowledge and Reasoning)
- Lecture 13: Probabilistic Reasoning (Uncertain Knowledge and Reasoning)
- Lecture 14: Probabilistic Reasoning over Time (Uncertain Knowledge and Reasoning)
- Lecture 15: Probabilistic Programming (Uncertain Knowledge and Reasoning)
- Lecture 16: Making Simple Decisions (Uncertain Knowledge and Reasoning)
- Lecture 17: Making Complex Decisions (Uncertain Knowledge and Reasoning)
- Lecture 18: Multiagent Decision Making (Uncertain Knowledge and Reasoning)
- Lecture 19: Learning from Examples (Machine Learning)
- Lecture 20: Learning Probabilistic Models (Machine Learning)
- Lecture 21: Deep Learning (Machine Learning)
- Lecture 22: Reinforcement Learning (Machine Learning)
- Lecture 23: Natural Language Processing (Communicating, Perceiving, and Acting)
- Lecture 24: Deep Learning for Natural Language Processing (Communicating, Perceiving, and Acting)
- Lecture 25: Computer Vision (Communicating, Perceiving, and Acting)
- Lecture 26: Robotics (Communicating, Perceiving, and Acting)
- Lecture 27: Philosophy, Ethics, and Safety of AI (Conclusions)
- Lecture 28: The Future of AI (Conclusions)