Dissertation (BSc Data Science &/w IPY) (G5260)
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Dissertation (BSc Data Science &/w IPY)
Module G5260
Module details for 2025/26.
30 credits
FHEQ Level 6
Module Outline
This module will give students the opportunity to complete an extensive project in Data Science under the supervision of a member of faculty. Students will be able to choose from a range of project topics or offer a project of their own. All topics will require the application of skills and knowledge gained through previous modules of study and will involve the student in the design and build of a technological solution to a Data Science related problem (using programming, modelling, simulation tools as appropriate). Some project topics will be available in collaboration with commerce and industry and will enable students to experience the methods and approaches of non-academic institutions. The teaching methods used will individual/small group meetings to discuss progress.
Module learning outcomes
Define a problem related to Data Science, and research
and demonstrate an understanding of the topic area.
Estimate, plan and manage time and resources, working within any constraints imposed by limited resources.
Specify, design, implement, test and evaluate an artifact using
computing technology and appropriate methods and tools.
Communicate and justify the problem and its analysis both orally and in writing.
Identify and apply appropriate professional and ethical standards, and show awareness of relevant legal and social issues.
Approach a complex task in a structured and logical manner using appropriate techniques and methods.
| Type | Timing | Weighting |
|---|---|---|
| Presentation | Spring Semester Week 10 Fri 16:00 | 15.00% |
| Dissertation (10000 words) | Semester 2 Assessment Week 1 Tue 16:00 | 85.00% |
Timing
Submission deadlines may vary for different types of assignment/groups of students.
Weighting
Coursework components (if listed) total 100% of the overall coursework weighting value.
| Term | Method | Duration | Week pattern |
|---|---|---|---|
| Autumn Semester | Personal Tutorial * | 1 hour | 11111111111 |
| Spring Semester | Personal Tutorial * | 1 hour | 1111111111 |
How to read the week pattern
The numbers indicate the weeks of the term and how many events take place each week.
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