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Unit information: Machine Learning in 2018/19

Please note: you are viewing unit and programme information for a past academic year. Please see the current academic year for up to date information.

Unit name Machine Learning
Unit code COMS30007
Credit points 10
Level of study H/6
Teaching block(s) Teaching Block 1 (weeks 1 - 12)
Unit director Dr. Ek
Open unit status Not open
Pre-requisites

None

Co-requisites

None

School/department Department of Computer Science
Faculty Faculty of Engineering

Description

Machine Learning is the science of how we can build abstractions of the world from data. In this unit we will start with the fundamental underlying principles and philosophies that allows us to learn and then look at how we can formulate these using explicit models.

Machine learning is mathematical in nature and a good grasp of linear algebra and multi-variate calculus is required to fully digest the material.

Intended learning outcomes

After successfully completing this unit, you will be able to understand the fundamental principles of machine learning and how to build models of data.

Teaching details

18 lectures; 9 lab sessions

Assessment Details

Exam and Coursework

Reading and References

Bishop, C. M. (2006). Pattern recognition and machine learning.

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