Linear Algebra for Data Science (MATH0101)

Key information

Faculty: Faculty of Mathematical and Physical Sciences
Teaching department: Mathematics
Credit value: 15

Restrictions: This course is aimed at students in the bio-sciences and neuroscience, who have A-level Mathematics or a good score in a Mathematics course taken in year one of the degree.
Timetable

Alternative credit options

There are no alternative credit options available for this module.

Description

This module introduces the basic ideas of linear algebra - vectors, matrices, systems of linear equations, bases, linear maps, eigenvalues and eigenvectors - illustrating the mathematics with examples drawn from data science such as least-squares solution of over-determined problems, linear differential equations and cluster analysis

Module deliveries for 2024/25 academic year

Intended teaching term: Term 2 听听听 Undergraduate (FHEQ Level 5)

Teaching and assessment

Mode of study: In person
Methods of assessment: 85% Exam

15% Coursework
Mark scheme: Numeric Marks

Other information

Number of students on module in previous year: 68
Module leader: Dr Luciano Rila
Who to contact for more information: math.ugteaching@ucl.ac.uk

Last updated

This module description was last updated on 8th April 2024.

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Important information

The catalogue has been updated with key information about the modules that will run during the 2024/25 academic session. Current and prospective students can browse through the catalogue to consider possible module choices for the coming year.

Please note,听information in the catalogue is听subject to change as teaching and assessment arrangements for 2024/25 may need to be adjusted in line with the University's Feedback and Assessment principles and operating model.

Centrally managed exam durations will be provided on students' individual exam timetables. Arrangements for locally managed exams and in-class activity will be confirmed by the teaching department for the module.

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