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 Duration 7 hours

Course Outline

The Evolution of Artificial Intelligence

  • Intelligent Agents

Problem-Solving Strategies

  • Solving Problems Through Search
  • Strategies Beyond Classical Search
  • Adversarial Search Techniques
  • Constraint Satisfaction Problems

Knowledge and Reasoning

  • Logical Agents
  • First-Order Logic
  • Inference Within First-Order Logic
  • Classical Planning
  • Planning and Acting in Real-World Scenarios
  • Knowledge Representation

Reasoning Under Uncertainty

  • Quantifying Uncertainty
  • Probabilistic Reasoning
  • Temporal Probabilistic Reasoning
  • Simple Decision-Making
  • Complex Decision-Making

Machine Learning

  • Learning from Examples
  • Integrating Knowledge in Learning
  • Learning Probabilistic Models
  • Reinforcement Learning

Communication, Perception, and Action

  • Natural Language Processing
  • Natural Language for Communication
  • Perception Systems
  • Robotics

Conclusions

  • Philosophical Foundations
  • AI: Current Landscape and Future Prospects

Requirements

Foundational understanding of computing, biology, mathematics, and physics

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