Artificial Intelligence

University of Cagliari

Academic year: 2026-2027

Instructors: Prof. Giorgio Fumera, Prof. Ambra Demontis

MSc programs in:

• Computer Engineering, Cybersecurity and Artificial Intelligence
• Electronic Engineering
• Internet Engineering

Official course description

Lecture schedule

• Tue., Sept. 29: Course introduction, search problems
• Thu., Oct. 1st: Search problems
• Tue., Oct. 6: Machine learning
• Thu., Oct. 8: Search problems
• Tue., Oct. 13: Machine Learning
• Thu., Oct. 15: Search problems. Knowledge and reasoning: logical languages
• Tue., Oct. 20: Machine Learning
• Thu., Oct. 22: Knowledge and reasoning: logical languages
• Tue., Oct. 27: Machine Learning
• Thu., Oct. 29: Knowledge and reasoning: logical languages
• Tue., Nov. 3: Machine Learning
• Thu., Nov. 5: Knowledge and reasoning: logical languages
• Tue., Nov. 10: Machine Learning
• Thu., Nov. 12: Knowledge and reasoning under unertainty: probabilistic models
• Tue., Nov. 17: Machine Learning
• Thu., Nov. 19: Bayesian networks
• Tue., Nov. 24: Machine Learning
• Thu., Nov. 26: Bayesian networks
• Tue., Dec. 1st: Machine Learning
• Tue., Dec. 15: Machine Learning

Lecture slides

Course introduction

Part I – Problem-solving, Knowledge and Reasoning (G. Fumera)

1. Search problems
2. Knowledge and reasoning: logical languages (slides available soon)
3. Knowledge and reasoning under unertainty: probabilistic models (Bayesian networks) (slides available soon)

Part II – Machine Learning (A. Demontis)

1. Introduction to Machine learning
2. Decision trees
3. Performance evaluation
4. Neural networks
5. Ensemble methods

Exercises

1. Search problems (available soon)
2. Knowledge and reasoning: logical languages (available soon)
3. Bayesian networks (available soon)
4. Machine learning

Next exams

• Mon., Oct. 26, 15:30 (only for students enrolled as “fuori corso”)