The course focuses on the study of fundamental concepts of machine learning, the main machine learning methods and software tools based on machine learning techniques. In particular, it aims at providing an understanding of the capabilities and limitations of these methods and tools, and to develop the ability to use some of the currently available technologies to solve problems of data analysis, knowledge extraction and decision support. Finally, it aims at discussing the main problems and opportunities that arise in contexts where the analysis extends to large volumes of data (Big Data).
teacher profile teaching materials
Introduction to machine learning
Types of machine learning
Methods for supervised and unsupervised learning
Model training and inference
Technologies and software tools for machine learning
Use of software tools for machine learning
Application of machine learning models with different types of datasets
Programme
Introduction to artificial intelligenceIntroduction to machine learning
Types of machine learning
Methods for supervised and unsupervised learning
Model training and inference
Technologies and software tools for machine learning
Use of software tools for machine learning
Application of machine learning models with different types of datasets
Core Documentation
Teaching materials provided by the lecturerAttendance
Attendance is not required, but it is recommended especially for easy learning to use the software toolsType of evaluation
The examination includes a computer-based test and the evaluation of a project