OVERVIEW

This module is dedicated to the study by the student of a specific use case of Machine Learning and Data Analysis related to robotics

AIMS AND CONTENT

LEARNING OUTCOMES

In this module, students will focus on the study of real use cases specifically related to robotics, on the basis of methodologies and insights discussed in the first module of the course

AIMS AND LEARNING OUTCOMES

The student will acquire skills in the study, development, solution of a real case study in the field of Machine Learning robotics and Data Analysis.

PREREQUISITES

Coding (Matlab/Python/R), linear algebra, probability and statistics

TEACHING METHODS

Project to be carried out independently or in groups of a maximum of two people.

SYLLABUS/CONTENT

1. Choice of a case study of Machine Learning and Data Analysis for robotics
2. Study of the state of the art and in-depth analysis of the case study
3. Case study solution through Machine Learning and Data Analysis techniques

RECOMMENDED READING/BIBLIOGRAPHY

F. X. Govers "Artificial intelligence for robotics: Build intelligent robots that perform human tasks using AI techniques" 2018

TEACHERS AND EXAM BOARD

LESSONS

LESSONS START

https://corsi.unige.it/10635/p/studenti-orario

Class schedule

The timetable for this course is available here: Portale EasyAcademy

EXAMS

EXAM DESCRIPTION

Oral by appointment

Students with learning disorders ("disturbi specifici di apprendimento", DSA) will be allowed to use specific modalities and supports that will be determined on a case-by-case basis in agreement with the delegate of the Engineering courses in the Committee for the Inclusion of Students with Disabilities.

ASSESSMENT METHODS

The student will solve a real problem at will (specifically related to robotics) by applying the techniques learned during the first module of the course.

Exam schedule