University of St Andrews

Key information

SCOTCAT credits : 15

ECTS credits : 7

Level : SCQF level 11

Semester: Both

Availability restrictions: Available only to students studying the PG Cert/PG Dip/MSc in Data Science (Digital)

Machine Learning enables computers to improve automatically with experience. A growing number of algorithms are being used to predict outcomes using patterns in collected data. This module covers the essential theory and algorithms, including mathematical foundations, and methodological approaches. It covers a variety of regression, classification and unsupervised approaches.

Learning and teaching methods and delivery

Weekly contact: Students should expect to engage in approximately six tutorials over the course of the module, which will be scheduled with an awareness of the pace at which they are progressing, rather than at a fixed time each week. Students should consider the amount of independent study time this module involves when planning their learning.

Scheduled learning hours: 6

Guided independent study hours: 148

Assessment pattern

As used by St Andrews: Coursework = 100%

As defined by QAA
Written examinations : 0%
Practical examinations : 0%
Coursework: 0%

Re-assessment: Coursework = 100%

Personnel

Module coordinator: Professor T W Kelsey
Module teaching staff: Dr Lei Fang

Intended learning outcomes

• be able to demonstrate the main concepts in machine learning
• demonstrate knowledge of important algorithms in the field and when to use them
• be able to apply machine learning to solve practical problems
• understand how to optimise algorithms for specific tasks