Description

Theory
2

Laboratory
2

Instructors

Veríssimo Santos

Contents

CP1: Introduction to artificial intelligence;
CP2: Introduction to Data Science;
CP3: Machine learning;
CP4: Types of learning;
CP5: Learning paradigms;
CP6: ML Tasks;
CP7: Evaluation of models;
CP8: Performance Metrics;
CP9: Models;
CP10: ML applications in the real world and in the Electrotechnical and Computer Engineering (ECE) area;
CP11: Overview of ML frameworks.

Learning Outcomes

The fundamental objectives of this UC are:
PO1 - Know and understand the area of artificial intelligence, as well as the main sub-areas and adjacent areas.
PO2 - Know and understand the main concepts and techniques in the field of automatic learning.
PO3: Integration and application of the main automatic learning techniques to real problems within the scope of Electrical Engineering, Electronics, Computers, Software development and related areas.