Artificial Intelligence: a modern approach

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This (20 hours) course is a reasoned overview on Artificial Intelligence, it is based on the new revised edition of the most widely adopted textbook on AI: Artificial Intelligence: a modern approach, by Stuart Russell and Peter Norvig. They will concentrate on a few selected topics with the aim to allow students to achieve a significant view on the basic ideas and techniques underlying the design of intelligent computer systems.   Starting from a historical perspective introduction the course will overview topics ranging over the four areas of AI: reasoning, learning, perceiving, and acting with a special focus on learning. 


  •        Introduction to AI – ( from chapters 1& 2) – 2h (What Is AI, The Foundations of AI,

The History of AI ,The State of the Art, Risks and Benefits of AI)

  •        Problem Solving overview: Search and Constraint Satisfaction Problems (from chapters 3&6) - 2h
  •        Knowledge, Reasoning and Planning overview (from chapters 7&10) - 2h
  •        Machine Learning: Learning from Examples – 1(from chapter 19) - 2h
  •        Machine Learning: Learning from Examples – 2 (from chapter 19) - 2h
  •        Machine Learning: Learning probabilistic models (from chapter 20) - 2h
  •        Machine Learning: Deep Learning: Simple and Convolutional Networks (from chapter 21) - 2h
  •        Machine Learning: Deep Learning: Recurrent Networks (from chapter 21) - 2h
  •        Perceiving and Acting: Deep Learning in NLP (from chapters 24&25) - 2h
  •        Ethical AI and Human-Centered AI (from chapter 27) - 2h

Educational aims

At the end of the course, the techniques learned will serve as the foundation for further study in AI and in AI-based application areas