Lecturer: Marco Piastra  

Course name: Artificial Intelligence
Course code: 504707
Degree course: Computer Engeneering
Disciplinary field of science: ING-INF/05
L'insegnamento è caratterizzante per: Computer Engeneering
University credits: ECTS 6
Course website: n.d.

Specific course objectives

This course introduces students to the fundamental elements of artificial intelligence as can be found in current knowledge representation, machine learning and problem solving techniques, with attention to algorithms and computational methods. Upon completion, students should be able to evaluate the potential of AI techniques for the design and engineering of state-of-the-art intelligent systems. They should also be able to read and understand most of the scientific and technical literature on the subject, with a substantial improvement of their self-learning capabilities in the discipline.

Course programme

The course follows a conceptual pathway organized in two main parts: the first part is an introduction to formal logic, both propositional and first-order, with a special focus on automatic calculus, while the second part is an introduction to the fundamental principles of machine learning and self-organizing systems.

Classical logic and automated symbolic reasoning

• Boolean algebras
• Logical language and semantical structures: logical consequence
• Deductive systems for propositional logic
• Decision problems and decidability
• Predicates and relations: first order logic
• Semi-decidability of first order logic
• First-order resolution with unification

Machine Learning

• Logic and probability: representation or statistics?
• The language of probability: representation
• Bayesian inference
• Graphical models and automated inference
• Probabilistic learning for graphical models: batch and online modes
• Reinforcement learning
• Clustering: K-means and related methods
• Self-organizing systems and applications

Course entry requirements

Basic mathematical skills, practical knowledge of at least one programming language, some acquaintance with algorithms and theoretical computer science.

Course structure and teaching

Lectures (hours/year in lecture theatre): 45
Practical class (hours/year in lecture theatre): 0
Practicals / Workshops (hours/year in lecture theatre): 0

Suggested reading materials

See the home page of the course for: lecture slides and notes, suggested readings, software for the exercises.

Testing and exams

The final exam is a 45-60 min interview about the theory of AI and the lab activities conducted.