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COMM424DA - Individual Research Project (2023)
MODULE TITLE | Individual Research Project | CREDIT VALUE | 60 |
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MODULE CODE | COMM424DA | MODULE CONVENER | Unknown |
DURATION: TERM | 1 | 2 | 3 |
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DURATION: WEEKS | 0 | 13 | 13 |
Number of Students Taking Module (anticipated) | 90 |
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This module will allow you to apply the knowledge learned in other modules in a significant data science project. You have two options for the selection of your project report:
Option 1. A research project carried out in the employer’s workplace as part of the apprentice’s day to day activities.
Option 2. If your employer does not support this activity as part of the Degree Apprenticeship, then you are free to complete another data science project on a topic of your choice. It may still be related to your organisation, or alternatively, it may be based on any other case study which allows you to collect data and complete theoretical analysis and/or practical software design and implementation. It may be based on your own idea or area of interest, or it could be on a topic proposed and defined by an Academic at the Computer Science Department of the University.
The module will develop your project planning, management and implementation skills as well as those in independent learning, presentation and writing. This will also be an opportunity to gain experience in the implementation of a data science project within your organisation or elsewhere, and to develop your understanding of the business requirements of such projects if you choose Option 1. The module further 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 and presentation of results.
Pre-requisites: Work-based project
Corequisites: None
This module is a part of the dual-qualification MSc Data Science (Professional) / Level 7 Research Scientist Apprenticeship programme. It cannot be taken as an elective by students on other programmes.
The apprenticeship standard and other documentation relating to the Level 7 Research Scientist Apprenticeship can be found here: https://www.instituteforapprenticeships.org/apprenticeship-standards/research-scientist-v1-0.
The project report is designed to demonstrate the application of knowledge and skills as it would in the occupation. It collates the raw research findings and demonstrates analysis (statistical and scientific), synthesis, evaluation, literature review and produces recommendations for the business to consider. The report is a significant and complex project in itself and thoroughly tests both higher and lower order knowledge and skills.
The module has several aims:
- To develop skills in project specification, planning and management
- To develop an understanding of appropriate data science tools to apply
- To consider the ethical issues associated with collecting, processing and analysing data
- To consolidate skills in the implementation of data science techniques
- To develop skills in the understanding and visualisation of the outputs of data science techniques
- To develop a greater understanding of where data science fits within the employer’s organisation (not valid for option 2)
- To develop presentation and writing skills
Most work will be independent study, but you will be supported by a supervisory team through regular meetings and progress reports. The supervisory team will normally consist of relevant academic faculty members from the MSc Data Science programme and, if you choose Option 1, a nominated individual at your employer’s organisation. In the latter case, ordinarily, the employer organisation will provide guidance on the business relevance of the project and together with the academic supervisor will identify project goals. Exceptionally, you may choose an academic data science project based on previously taught module content. In this scenario, the supervisory team will consist solely of an academic supervisory from the MSc Data Science programme.
Work towards project goals will be carried out independently over a 9-month period, supported by regular supervision meetings conducted using online tools (e.g. video conferencing). A number of “project days” will bring all the cohort together on campus to present progress and hold meetings with academic supervisors. Interim and final presentations of project findings will form part of the project assessment, which will be completed with a substantial report.
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. Design and follow systematically the phases of research project development.
3. Apply sophisticated and appropriate analysis and development techniques at each stage of a project.
Discipline Specific Skills and Knowledge
4. Show familiarity with the background and context of a new application area.
5. Produce full documentation as appropriate to the system and research.
6. Work in an interdisciplinary area.
Personal and Key Transferable / Employment Skills and Knowledge
7. Conduct independent study, including library and web-based research.
8. Reflect critically on processes and products.
9. Plan an extended project and manage time effectively.
10. Present work to a non-specialist audience.
Activities related to this module will include:
- Introduction to the module;
- Identification of suitable projects from within the student’s organisation or based on previous taught content;
- Creation of a project plan and specification with your supervisor team;
- Implementation of the project;
- Presentation of progress updates to student and supervisor;
- Meetings with academic supervisor (face-to-face and/or online);
- Final submission: a report and final presentation.
Scheduled Learning & Teaching Activities | 14.00 | Guided Independent Study | 586.00 | Placement / Study Abroad | 0.00 |
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Category | Hours of study time | Description |
Scheduled Learning Teaching Activities | 2 | Introductory Session |
Scheduled Learning Teaching Activities | 12 | Supervisory meetings |
Guided Independent Learning | 300 | Project work |
Guided Independent Learning | 286 | Background reading and private study |
Form of Assessment | Size of Assessment (e.g. duration/length) | ILOs Assessed | Feedback Method |
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Supervisor Meetings | 12 | 1-10 | Oral |
Coursework | 70 | Written Exams | 0 | Practical Exams | 30 |
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Form of Assessment | % of Credit | Size of Assessment (e.g. duration/length) | ILOs Assessed | Feedback Method |
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Project Proposal | 10 | Max 4 pages | 1, 7, 9 | Written |
Final presentation | 20 | 15 minutes | 1-9 | Written |
Final Report | 70 | Max 10 pages | 2-7,10 | Written |
Original Form of Assessment | Form of Re-assessment | ILOs Re-assessed | Time Scale for Re-assessment |
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Project Porposal | Project proposal | 1, 7, 9 | Within 8 weeks |
Final presentation | Presentation | 1-8, 10 | Within 8 weeks |
Final Report | Resubmitted final report | 1-9 | Within 8 weeks |
information that you are expected to consult. Further guidance will be provided by the Module Convener
Not applicable
Reading list for this module:
There are currently no reading list entries found for this module.
CREDIT VALUE | 60 | ECTS VALUE | 30 |
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PRE-REQUISITE MODULES | None |
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CO-REQUISITE MODULES | None |
NQF LEVEL (FHEQ) | 7 | AVAILABLE AS DISTANCE LEARNING | No |
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ORIGIN DATE | Monday 11 October 2021 | LAST REVISION DATE | Wednesday 01 November 2023 |
KEY WORDS SEARCH | None Defined |
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