2021/22 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, Semester 1 (Sep to Jan) View Timetable
Year running 2021/22
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
Learning outcomes:
This specifies the content that it is expected a student will know (or will have learnt) and the skills explicitly developed during the module. The learning outcomes will relate to the level of the module and will link to the key assessment tasks in the module. Learning outcomes should be specific, measurable, and attainable, and use action verbs. 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
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 |
| Seminar | 10 | 1.00 | 10.00 |
| Private study hours | 120.00 | ||
| Total Contact hours | 30.00 | ||
| 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 | 20.00 |
| Assignment | Coursework 2 | 40.00 |
| Total percentage (Assessment Coursework) | 60.00 | |
This module will be reassessed by an online time-constrained assessment
Exams
| Exam type | Exam duration | % of formal assessment |
| Online Time-Limited assessment | 2 hr | 40.00 |
| Total percentage (Assessment Exams) | 40.00 | |
This module will be reassessed by an online time-constrained assessment.
Reading list
The reading list is available from the Library websiteLast updated: 15/03/2022 16:12:19
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- Undergraduate module catalogue
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