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 use cases specifically related to Robotics, on the basis of methodologies and insights discussed in the accompanying main module.

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.

During the course the following skills will be developed
- personal competence
- social competence
- ability to learn to learn
- competence in project creation
- competence in project management

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 (to develop ability to learn to learn, personal competence, social competence, competence in project creation, and competence in project management)

For working students and students with certification of Specific Learning Disabilities (SLD), disabilities, or other special educational needs are advised to contact the instructor at the beginning of the course to arrange teaching and examination methods that, while respecting the teaching objectives, take into account individual learning styles.

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

Exam Board

LUCA ONETO (President)

FABIO ROLI

DAVIDE ANGUITA (President Substitute)

LESSONS

LESSONS START

https://easyacademy.unige.it/portalestudenti/index.php?view=easycourse&_lang=it&include=corso​

Class schedule

The timetable for this course is available here: Portale EasyAcademy

EXAMS

EXAM DESCRIPTION

Oral by appointment

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