Machine Learning, 7.5 Credits

Machine learning is a subfield of artificial intelligence within computer science and includes techniques that enable machines (robots or software) to learn how to perform specific tasks based on data, rather than through explicit programming. Applications include image classification, predictive maintenance, text analysis, speech recognition, and the generation of images and text.

This course provides an introduction to machine learning with the aim of developing an understanding of fundamental concepts, methods, and algorithms. This is achieved through hands-on work in which algorithms are implemented and modified almost from scratch, as well as through the study of data analysis, data preprocessing, model evaluation, identification of potential issues and misleading results, and practical recommendations for applying machine learning techniques.

The course also includes a literature study that provides insight into current research, as well as a practical classification task and a final project that offer practical experience and skills for further studies in academia or professional work in industry with machine learning.

ECTS Credits

7.5 Credits

Level of education

First cycle, has less than 60 credits in first-cycle course/s as entry requirements (G1F)

School

School of Science and Technology