Postgraduate Course: Data Science in Clinical Research: Research Project (PAMA11083)
Course Outline
| School | Deanery of Clinical Sciences |
College | College of Medicine and Veterinary Medicine |
| Credit level (Normal year taken) | SCQF Level 11 (Postgraduate) |
| Course type | Online Distance Learning |
Availability | Not available to visiting students |
| SCQF Credits | 40 |
ECTS Credits | 20 |
| Summary | The course, the third of three co-requisites, is designed to develop the student's academic skills and ability to apply scientific theory. Students will build on knowledge gained in the first two courses to undertake a research project using data science analytical methods. This course is designed to develop the student¿s ability to think scientifically and to develop their scientific written skills through the completion of a research report that follows expected academic conventions of style, tone, structuring and referencing. |
| Course description |
The types of activity involved in each project will vary but will include most of the following:
- analysing and extending relevant theory in novel ways
- designing and implementing experimental solutions
- discussing existing results and presenting new research
- developing written and oral presentation skills
The activity will be supervised by a clinical academic within the University Department of Anaesthesia, Critical Care and Pain and a co-supervisor with expertise in data science/informatics. We encourage co-supervision from the public sector (e.g. NHS) and industry, from which we anticipate a fruitful supply of appropriately challenging research topics.
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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 2017/18, Not available to visiting students (SS1)
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Quota: None |
| Course Start |
Semester 1 |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
400
(
Dissertation/Project Supervision Hours 9,
Programme Level Learning and Teaching Hours 8,
Directed Learning and Independent Learning Hours
383 )
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| Assessment (Further Info) |
Written Exam
0 %,
Coursework
100 %,
Practical Exam
0 %
|
| Additional Information (Assessment) |
Written Exam 0 %
Coursework 100 %
Practical Exam 0 %
|
| Feedback |
Not entered |
| No Exam Information |
Learning Outcomes
On completion of this course, the student will be able to:
- Discuss and solve conceptual problems which arise during the investigation; justify design decisions made during the investigation.
- Undertake analyses using data science analytical methods
- Critically evaluate the research they have undertaken, review their findings in the context of existing literature and comprehensively present their work.
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Additional Information
| Graduate Attributes and Skills |
Not entered |
| Keywords | Research project,data science,clinical medicine |
Contacts
| Course organiser | Dr Nazir Lone
Tel:
Email: nazir.lone@ed.ac.uk |
Course secretary | Mrs Ruth Macdonald
Tel: (0131) 242 3135
Email: Ruth.MacDonald@ed.ac.uk |
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