Postgraduate Course: MSc Dissertation (Data Science for Biology) (PGBI11133)
Course Outline
| School | School of Biological Sciences |
College | College of Science and Engineering |
| Credit level (Normal year taken) | SCQF Level 11 (Postgraduate) |
| Course type | Dissertation |
Availability | Not available to visiting students |
| SCQF Credits | 60 |
ECTS Credits | 30 |
| Summary | This is an essential component of the MSc programme. Students carry out a substantial piece of research work within an individual research laboratory. This work is supervised by the dissertation project supervisor(s) and leads to a dissertation. |
| Course description |
This project allows students to take an individual research project. On this project they apply and develop the skills they have learned in the taught component to an individual research project.
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Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
|
Co-requisites | |
| Prohibited Combinations | |
Other requirements | None |
Course Delivery Information
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| Academic year 2024/25, Not available to visiting students (SS1)
|
Quota: 60 |
| Course Start |
Block 5 (Sem 2) and beyond |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
600
(
Lecture Hours 6,
Seminar/Tutorial Hours 14,
Programme Level Learning and Teaching Hours 12,
Directed Learning and Independent Learning Hours
568 )
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| Assessment (Further Info) |
Written Exam
0 %,
Coursework
100 %,
Practical Exam
0 %
|
| Additional Information (Assessment) |
Dissertation (90%)
Supervisor assessment (10%) |
| Feedback |
Students will be kept informed of their progress typically by verbal feedback during the dissertation. Written feedback will also be provided on one draft submission of the dissertation that typically takes place a week before the final submission. |
| No Exam Information |
Learning Outcomes
On completion of this course, the student will be able to:
- Develop written and oral presentation skills and use them to present research outcomes.
- Design and execute experiments.
- Organise and plan their time in order to complete a program of work within a constrained time-frame.
- Apply data science skills learned on the program to a specific research question.
- Explore and interpret the relevant literature to their project and integrate this with their research outcomes.
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Additional Information
| Graduate Attributes and Skills |
KNOWLEDGE AND UNDERSTANDING: A critical awareness of current issues in a subject/discipline/sector and one or more specialisms.
PRACTICE: APPLIED KNOWLEDGE, SKILLS AND UNDERSTANDING: In planning and executing a significant project of research, investigation or development.
GENERIC COGNITIVE SKILLS: Develop original and creative responses to problems and issues. Critically review, consolidate and extend knowledge, skills, practices and thinking in a subject/discipline/sector. Deal with complex issues and make informed judgements in situations in the absence of complete or consistent data/information.
COMMUNICATION, ICT AND NUMERACY SKILLS: Use a wide range of routine skills and a range of advanced and specialised skills as appropriate to a subject/discipline/sector. Communicate with peers, more senior colleagues and specialists. Use a wide range of ICT applications to support and enhance work at this level and adjust features to suit purpose. Undertake critical evaluations of a wide range of numerical and graphical data. |
| Keywords | Not entered |
Contacts
| Course organiser | Dr Simon Tomlinson
Tel: (0131 6)51 7252
Email: simon.tomlinson@ed.ac.uk |
Course secretary | Mr Alex Ramsay
Tel:
Email: gramsay3@ed.ac.uk |
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