Module code: DAT6501
Credits: 30.0
Semester: SEM1
Contact: Dr Seth Zenz
In this module, you will learn about cutting-edge developments in the fields of machine learning and artificial intelligence, and how they are being used to solve difficult or previously intractable problems. The aim is to give you an appreciation and background knowledge of what machine learning techniques are capable of, what the most powerful current techniques are, how they work, how they can go wrong, and how you can implement them to solve problems yourself. This module is taught through a combination of lectures on the theory and operation of modern machine learning and AI techniques, and computer lab projects where you will implement such methods as random forests, support vector machines, convolutional neural networks, and generative adversarial networks to solve problems in physics and related fields that would be difficult to address using more traditional analysis techniques.
Connected course(s): UDF DATA
Assessment: 100.0% Coursework
Level: 6
