DSC-10001 - Foundations of Data Science
Coordinator: Peter Wootton Room: MAC2.21 Tel: +44 1782 7 33767
Lecture Time:
Level: Level 4
Credits: 30
Study Hours: 300
School Office: 01782 733075

Programme/Approved Electives for 2026/27

None

Available as a Free Standing Elective

No

Co-requisites

None

Prerequisites

None

Barred Combinations

None

Description for 2026/27

Mathematics underpins much of modern day Data Science and is a quantitative language for how to discuss concepts and ideas in a formal setting. This module will introduce students to areas of Mathematics most relevant to these areas, including vectors and matrices, functions, graph theory, logic, information theory, probability and statistics, as well as a toolbox of essential mathematical techniques.
Students will learn how mathematical abstractions can be used to represent real world scenarios, develop skills to reason about such models, and learn problem solving skills and proof strategies. This allows students to use mathematics as an effective means of communication when solving real world problems.

Aims
The module aims to introduce students to mathematical problem solving skills, useful in a range of contexts, with a particular focus on Data Science. Students will develop experience with representing real world problem domains by using mathematical abstractions, and they will learn the skills and techniques required for analysing such systems as well as studying fundamentals that underpin all Data Science techniques and applications.

Intended Learning Outcomes

Model and analyse real world problems using mathematical abstractions and construct basic mathematical proofs: 2,3
Demonstrate mathematical problem solving skills in a variety of domains: 1,2,3
Apply mathematical methods and techniques involving functions, vectors, calculus, trigonometry and algebra: 3
Apply abstract data structures (such as sets, relations, and graphs) and basic statistical techniques to represent, summarise, solve and interpret computational problems: 1,2

Study hours

60 hours of lectures
24 hours of tutorials
48 hours of tutorial preparation
25 hours of class test revision
50 hours of exam revision
50 hours completing problem sheets
43 hours of consolidation study

School Rules

None

Description of Module Assessment