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DATA SCIENCE AND TECHNOLOGY INTELLIGENCE Single discipline educational activity
Course Sheet Academic Year of enrolment:
Professor and Collaborators:
Hours of classroom activity:
Prerequisites:
For a full understanding of the topics covered, knowledge of the contents of the “Applied Data Analytics” course is strongly recommended.
Objectives Contents The course is divided into two modules. In the first, concepts relating to Data Science and Artificial Intelligence will be introduced, discussing their applications in various contexts, and subsequently focusing on Machine Learning (ML), supervised classification and evaluation metrics of machine learning systems.
Extended Syllabus Module 1. Elements of Data Science, Artificial Intelligence and Machine Learning
Module 2. Practical applications and case studies
Recommended Bibliography Course material will be provided in the form of lecture slides, which will be uploaded to the e-learning portal, and readings (articles, tutorials or part of books) indicated by the teacher during the course.
Methods of Provision Teaching Methods The course is composed by 36 hours of lectures.
Evaluation methods Verification of learning:
The exam will include a multiple choice and/or open question test to evaluate the understanding of the topics covered, a practical test to evaluate the understanding and ability to use the software tools covered, and a short oral interview.
