Study information

Dissertation Project - 2024 entry

MODULE TITLEDissertation Project CREDIT VALUE60
MODULE CODEMTHM064 MODULE CONVENERUnknown
DURATION: TERM 1 2 3
DURATION: WEEKS 12 5
Number of Students Taking Module (anticipated) 40
DESCRIPTION - summary of the module content

In this module, you will work on a research problem in the application of Data Science. You will apply your understanding of the underlying concepts of Data Science together with the methods and tools that you have learned to a problem in an applied field. The project will require understanding of the setting, a critical review of possible approaches, choice of appropriate methodology, an extended piece of data analysis and a clear and concise write up of the background, data, methodology, results and conclusions. This is an independent project, supervised by an expert from the relevant area, which culminates in writing a dissertation, describing the research and its results. Research topics can be selected from across the breadth of the application of Data Science and Supervisors may be based in either the Department Mathematics and Statistics or Computer Science.

 

AIMS - intentions of the module

This module aims to give you in-depth experience of applying Data Science and Statistics to real-world problems, preparing you for work in a commercial setting or further post-graduate work. The module aims to build on the knowledge and skills you have acquired in the taught modules of the programme to allow you to investigate an area of particular interest to you. It aims to give you experience of many aspects of research work, including problem formulation, literature review, planning, tool development, experimentation, analysis, interpretation and presentation of results.

 

INTENDED LEARNING OUTCOMES (ILOs) (see assessment section below for how ILOs will be assessed)

On successful completion of this module you should be able to:

Module Specific Skills and Knowledge

1. Demonstrate knowledge of a research topic of relevance to your MSc programme, acquired through a deep and self-motivated exploration of that topic; 
2. Apply sophisticated and appropriate analysis and development techniques at each stage of a project, providing full documentation as appropriate to the system and research;

Discipline Specific Skills and Knowledge

3. Show familiarity with the background and context of a new application area; 
4. Apply methods and tools learnt in the context of other fields to the application in question;

Personal and Key Transferable / Employment Skills and Knowledge

5. Plan an extended project and manage time effectively;
6. Report writing and presentation of work to a non-specialist audience. 

 

SYLLABUS PLAN - summary of the structure and academic content of the module

Not applicable

LEARNING AND TEACHING
LEARNING ACTIVITIES AND TEACHING METHODS (given in hours of study time)
Scheduled Learning & Teaching Activities 20 Guided Independent Study 580 Placement / Study Abroad 0
DETAILS OF LEARNING ACTIVITIES AND TEACHING METHODS
Category Hours of study time Description
Scheduled learning and teaching activities 20 Project supervision
Guided Independent Study 580 Individual assessed work

 

ASSESSMENT
FORMATIVE ASSESSMENT - for feedback and development purposes; does not count towards module grade
Form of Assessment Size of Assessment (e.g. duration/length) ILOs Assessed Feedback Method
Two page project proposal in the early stages of project  2 pages All Oral

 

SUMMATIVE ASSESSMENT (% of credit)
Coursework 100 Written Exams 0 Practical Exams 0
DETAILS OF SUMMATIVE ASSESSMENT
Form of Assessment % of Credit Size of Assessment (e.g. duration/length) ILOs Assessed Feedback Method
Coursework – Mid Point Presentation  10 10 mins 1,3,6 Written
Coursework – Final Presentation 20 10 mins 1,3,6 Written
Coursework – Dissertation 70 30-40 pages 1-6 Written

 

DETAILS OF RE-ASSESSMENT (where required by referral or deferral)
Original Form of Assessment Form of Re-assessment ILOs Re-assessed Time Scale for Re-assessment
All above Coursework - Dissertation 1-6 To be agreed by consequences of failure meeting

 

RE-ASSESSMENT NOTES
RESOURCES
INDICATIVE LEARNING RESOURCES - The following list is offered as an indication of the type & level of
information that you are expected to consult. Further guidance will be provided by the Module Convener

Basic reading:

  • Succeeding with your masters dissertation – John Biggam

ELE:

 

Web based and Electronic Resources:

 

Other Resources:

 

Reading list for this module:

There are currently no reading list entries found for this module.

CREDIT VALUE 60 ECTS VALUE 30
PRE-REQUISITE MODULES None
CO-REQUISITE MODULES None
NQF LEVEL (FHEQ) 7 AVAILABLE AS DISTANCE LEARNING No
ORIGIN DATE Wednesday 31st July 2024 LAST REVISION DATE Wednesday 18th December 2024
KEY WORDS SEARCH Statistics, Data Science, Dissertation, Research Project

Please note that all modules are subject to change, please get in touch if you have any questions about this module.