96150 - LABORATORY OF ARTIFICIAL INTELLIGENCE APPLICATIONS M

Learning outcomes

The course aims to providesome general knowledge about fundamentals methods and techniques of the Artificial Intelligence (AI), and how these approaches can provide innovative solutions to classic industrial problems.

To this end, after an introduction about philosophical and ethic aspects of AI, the course will introduce AI models and methods that are commonly adopted in the development of software systems.

The students will experiment in the labs the use of specific tools and techniques, by applying them to case studies.

Course contents

Contents

The course is strucutred along three main parts:

• Introduction to the Python language, and to the Jupyter/JupyterLab framework
  
• Introduction to AI algorithms for solution search in the state space (Problem solving through search in the state space; Constraints Satisfaction Problems)
• Introduction to some Machine Learning algorithms (Linear Models and Generalized Linear Modells; Decision Trees and Ensemble methods; simple Neural Networks; Density Estimation)

Prerequisites

Attending the course does not require any mandatory prerequisite. However, from a more cultural viewpoint, it is suggested (but not mandatory) to attend the course "METODI E MODELLI DI DATA ANALYTICS M".

It is also assumed that the prospective student already has some background knowledge about Object Oriented Programming.

All the lessons, the materials and the exams will be in english.

Readings/Bibliography

Materials will be published in the form of the course slides, and they will accessible through the platform virtuale.unibo.it

Books:

• S. Russel. P. Norvig. Artificial Intelligence A Modern Approach. Fourth Edition, 2022, Pearson.
• Flach, Peter. Machine learning: the art and science of algorithms that make sense of data. Cambridge university press, 2012.

Teaching methods

The teaching is mainly given in the labs, with some lessons given by the teachers, and practical activities under the teachers' supervision.

Given the type of activities that will be given in laboratories, students attending this course are requested to take the additional courses Module 1 and Module 2 about safety in work environments, [https://elearning-sicurezza.unibo.it/] in e-learning modality.

Assessment methods

The test (at the end of the course) aims to assess the acquisition of the knowledge and competencies w.r..t. the course topics.

The test is organized as a presentation of a case study (assigned bu the teacher) where the student illustrates which techniques have been applied, why, and comments the obtained results.

To attend the test, it is mandatory to book it through the platform AlmaEsami, few days before the deadline of each test. Ina case student would fail to book for a test within the deadline, but she/he would be strongly motivated to attend the test, the student is invited to directly contact the teachers via the institutional email. Once each test is corrected, and the marks are published, each student will have few days to decide to refuse it. Otherwise, the mark will be considered as accepted.

Teaching tools

• Materials (slides, excerises, ...) will be downloadable thorugh the platform virtuale.unibo.it

• If needed, the platform Microsoft Teams will be used

Further tools that will be used during the course:

• Python3
• VSCode
• Thonny
• Jupyter/JupyterLab
  

Office hours

See the website of Federico Chesani

See the website of Michele Lombardi