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2022/23 Taught Postgraduate Module Catalogue

COMP5122M Data Science

15 creditsClass Size: 315

Module manager: Professor Roy Ruddle

Taught: Semester 1 (Sep to Jan) View Timetable

Year running 2022/23

This module is not approved as an Elective


The aim of the module is for students to understand methods of analysis that allow people to gain insights from complex data. The module covers the theoretical basis of a variety of approaches, placed into a practical context using different application domains.

Learning outcomes
Learning outcomes:
1. Understand the work of a data scientist
2. Understand issues relating to data governance
3. Understand how to acquire, link and investigate the quality of data
4. Apply problem-solving skills to effectively analyse data and communicate findings for a given application scenario
5. Understand how analysis workflows may be scaled up to meet the challenges posed by Big Data


Overview: Work context and core skills of a data scientist (problem-solving; statistics; business acumen; communication). Data governance: ethics, privacy, regulations, policies, and provenance. Analysis lifecycle: problem understanding, data acquisition (data types; record linkage; Open Data), data quality (completeness, correctness, concordance, currency & plausibility), analysis techniques, and communicating the results. Practical application using case studies drawn from different application domains such as R and Tableau. Scale-up of analysis for Big Data.

Teaching methods

Delivery typeNumberLength hoursStudent hours
Private study hours130.00
Total Contact hours20.00
Total hours (100hr per 10 credits)150.00

Private study

Some of this centres on the practical work that underpins the module and the coursework. Students will also be provided with a recommended reading list including books, papers and online resources. They will receive guidance on where to focus this reading and advice on how it links to module content.

Opportunities for Formative Feedback

Contribution to seminars (typically weekly). Progress in practicals (typically weekly). Engagement and standard of coursework.

Methods of assessment

Assessment typeNotes% of formal assessment
AssignmentCoursework 120.00
AssignmentCoursework 240.00
Total percentage (Assessment Coursework)60.00

Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated

Exam typeExam duration% of formal assessment
Online Time-Limited assessment2 hr 40.00
Total percentage (Assessment Exams)40.00

This module will be reassessed by an online time-limited assessment.

Reading list

The reading list is available from the Library website

Last updated: 01/06/2022 16:59:02


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