MAT-10055 - Mathematical Techniques for Data Science
Coordinator: Sergei Annenkov Tel: +44 1782 7 33078
Lecture Time: See Timetable...
Level: Level 4
Credits: 30
Study Hours: 300
School Office: 01782 733075

Programme/Approved Electives for 2024/25

None

Available as a Free Standing Elective

No

Co-requisites

None

Prerequisites

N/A

Barred Combinations

N/A

Description for 2024/25

The material in this module will introduce students to fundamental mathematical concepts and styles of thinking that underpin the theory behind many of the algorithms and statistical techniques used in data science, which they will meet in later levels of study.

Aims
The module aims to provide students with the mathematical techniques and skills that are required for the Data Science programme, in particular preparing students for the levels 5 and 6 mathematics modules on offer. The module takes account of the fact that the majority of students on the programme will not have taken A-Level Mathematics.

Intended Learning Outcomes

use mathematical skills and techniques to solve problems;: 1,2,3
draw diagrams and sketch graphs to help explore mathematical situations and interpret solutions;
: 2,3
make deductions and inferences and draw conclusions by using mathematical reasoning;
: 1,2,3
represent situations mathematically and understand the mathematical models that may be applied to solve them.: 1,2,3

Study hours

60 hours of structured lectures, 20 hours of student activity classes, and 220 hours of independent study comprising 40 hours class test preparation, 60 hours preparation and completion of online activities and 120 hours (60 hours per semester) of consolidation of material.

School Rules

None

Description of Module Assessment

1: Computer Task weighted 60%
Maple TA assessment


2: Class Test weighted 20%
Class Test


3: Class Test weighted 20%
Class Test