96150 - LABORATORY OF ARTIFICIAL INTELLIGENCE APPLICATIONS M

Academic Year 2022/2023

  • Moduli: Federico Chesani (Modulo 1) Michele Lombardi (Modulo 2)
  • Teaching Mode: Traditional lectures (Modulo 1) Traditional lectures (Modulo 2)
  • Campus: Bologna
  • Corso: Second cycle degree programme (LM) in Engineering Management (cod. 0936)

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

Prerequisites

It si strongly suggested to attend and positively pass the exam of  "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.

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)

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 classrooms, with some activities that will be held in laboratories using faculty computers.

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 will be organized into two parts: a first one, in the form of open questions and written answers; and a second one more practical, and that will be held using a computer.

The test (the two parts together) will last 120 minutes, approximately, and during the test it will be strictly forbidden to use books and/or private notes. The test is successfully passed with a grade of 18/32, with a maximum of 32/32 (but the final mark will be on the basis of /30).

More details will be provided during the classrooms, and also in the notes published on the virtuale platform.

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

SDGs

Quality education Decent work and economic growth Industry, innovation and infrastructure

This teaching activity contributes to the achievement of the Sustainable Development Goals of the UN 2030 Agenda.