CSC-40072 - Mathematics for AI and Data Science
Coordinator: Sergei Annenkov Tel: +44 1782 7 33078
Lecture Time: See Timetable...
Level: Level 7
Credits: 15
Study Hours: 150
School Office: 01782 733075

Programme/Approved Electives for 2024/25

None

Available as a Free Standing Elective

No

Co-requisites

None

Prerequisites

None

Barred Combinations

None

Description for 2024/25

This module aims to give students from non-mathematical backgrounds an introduction to the mathematical concepts relevant to AI and data science. It will provide students with the necessary knowledge and skills to tackle real world AI and data science problems including topics such as quadratic equations; vectors, matrices; linear questions and multiple variables; functions and probability.

Aims
This module aims to give students from non-mathematical backgrounds an introduction to the mathematical concepts relevant to AI and Data Science.

Intended Learning Outcomes

critically appraise various mathematical approaches to analysing a given data set;: 1,2
select and apply suitable techniques to solve relevant AI and Data Science problems in calculus, linear algebra, and probability;: 1,2
analyse and apply periodic functions;: 1,2
summarise how mathematical approaches can be applied to AI and Data Science problems: 2

Study hours

10 x 2 hours of lectures
10 x 1 hours of practicals/problem classes
90 hours independent study
30 hours report preparation

School Rules

None

Description of Module Assessment

1: Online Tasks weighted 25%
Set of 5 online weekly tasks


2: Report weighted 75%
Report outlining steps and reasons taken to solve a set of problems and presentation of the results.