2020/21 Taught Postgraduate Module Catalogue

COMP5122M Data Science

15 creditsClass Size: 300

Module manager: Roy Ruddle
Email: r.a.ruddle@leeds.ac.uk

Taught: 1 Jun to 30 Sep, 1 Sep to 31 Jan (adv yr), Semester 2 (Jan to Jun) View Timetable

Year running 2020/21

This module is not approved as an Elective

Objectives

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
On completion of this module, students should be able to:
- Understand the work of a data scientist
- Understand issues relating to data governance
- Understand how to acquire, link and investigate the quality of data
- Apply problem-solving skills to effectively analyse data and communicate findings for a given application scenario
- Understand how analysis workflows may be scaled up to meet the challenges posed by Big Data

Syllabus

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 (http://www.tableausoftware.com/data-visualization-software; provided through the Tableau for teaching programme). Scale-up of analysis for Big Data.

Teaching methods

Delivery type	Number	Length hours	Student hours
Lecture	10	1.00	10.00
Practical	10	1.00	10.00
Private study hours			130.00
Total Contact hours			20.00
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

Coursework

Assessment type	Notes	% of formal assessment
Assignment	Coursework 1	10.00
Assignment	Coursework 2	20.00
Assignment	Coursework 3	30.00
Assignment	Coursework 4	40.00
Total percentage (Assessment Coursework)		100.00

This module will be reassessed by an online time-constrained assessment

Reading list

The reading list is available from the Library website

Last updated: 12/07/2021

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