FOUNDATIONS OF ARTIFICIAL INTELLIGENCE
cod. 1009065

Academic year 2023/24
1° year of course - Second semester
Professor
Eleonora IOTTI
Academic discipline
Informatica (INF/01)
Field
Discipline informatiche
Type of training activity
Characterising
48 hours
of face-to-face activities
6 credits
hub:
course unit
in ITALIAN

Learning objectives

The main goal of the course is to provide basic mathematical and algorithmic tools to allow the effective study of Artificial Intelligence (AI) topics and research. On the second hand, the course aims to lay the foundations for attending the next courses of AI.
According to Dublino Descriptors, students at the end of the course are capable of:
1. understand the theoretical basis of AI; know and remember the notations used in scientific literature regarding AI
2. apply theoretical knowledges to develop simple algorithms; use the major AI software libraries; reuse the code of algorithms in literature and customize it
3. evaluate and compare different approaches to a problem; recognize the techniques used in an AI algorithm
4. communicate the motivations behind the choices made to deal with an AI problem; describe the techniques used to deal with an AI problem
5. learning other approaches and techniques of AI, even if not basic; read and understand a scientific paper on the topics of the course

Prerequisites

Calculus, linear algebra and basic of computer programming.

Course unit content

The course offers to discuss and elaborate on some of the mathematical foundations of Artificial Intelligence, by proposing selected topics and examples

Full programme

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Bibliography

Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep learning. MIT press (url: https://www.deeplearningbook.org/)
CS231n: Convolutional Neural Networks for Visual Recognition. Stanford course (url: https://cs231n.github.io/convolutional-networks/)
Nielsen, M. A. (2015). Neural networks and deep learning. Determination press (url: http://neuralnetworksanddeeplearning.com/)
Additional educational material will be provided by the teacher

Teaching methods

Lectures. Lecture notes will be uploaded every week on Elly platform and will be considered as a part of the teaching material

Assessment methods and criteria

Critical discussion on the development of an assignment given to the student, following an oral exam on all topics of the course. The assignment is chosen after the student enrolls in the exam, in agree with the teacher, and it is an individual work

Other information

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2030 agenda goals for sustainable development

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