University Homepage
DRPS Homepage
DRPS Search
DRPS Contact
DRPS : Course Catalogue : School of Informatics : Informatics

Postgraduate Course: MSc by Research Thesis (Data Science) (INFR11106)

Course Outline
SchoolSchool of Informatics CollegeCollege of Science and Engineering
Credit level (Normal year taken)SCQF Level 11 (Postgraduate)
Course typeDissertation AvailabilityNot available to visiting students
SCQF Credits90 ECTS Credits45
SummaryStudents will pursue an eight-month research project in Data Science which results in a written dissertation. The research must demonstrate competence, knowledge, and be presented in a critical and scholarly way, demonstrating that the student is capable of undertaking independent research.
Course description Project dependent.
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Co-requisites
Prohibited Combinations Other requirements For students on the MSc by Research in Data Science only.
Course Delivery Information
Academic year 2018/19, Not available to visiting students (SS1) Quota:  None
Course Start Block 5 (Sem 2) and beyond
Timetable Timetable
Learning and Teaching activities (Further Info) Total Hours: 900 ( Seminar/Tutorial Hours 10, Dissertation/Project Supervision Hours 25, Programme Level Learning and Teaching Hours 18, Directed Learning and Independent Learning Hours 847 )
Assessment (Further Info) Written Exam 0 %, Coursework 100 %, Practical Exam 0 %
Additional Information (Assessment) Written Exam 0 %, Coursework 100 %, Practical Exam 0 %

The project is assessed completely on the basis of a written thesis which should typically contain:

Title page with abstract (a one or two paragraph summary of the contents).

Introduction : background, previous work, exposition of relevant literature, setting of the work in the proper context.

Description of the work undertaken : this may be divided into chapters describing the conceptual design work and the actual implementation separately. Any problems or difficulties and the suggested solutions should be mentioned. Alternative solutions and their evaluation should also be included.

Analysis : results and their critical analysis should be reported, whether the results conform to expectations or otherwise and how they compare with other related work.

Conclusion : concluding remarks and observations, unsolved problems, suggestions for further work.


Students may be required by their project markers to demonstrate any system that arose from the project.
Feedback Not entered
No Exam Information
Learning Outcomes
On completion of this course, the student will be able to:
  1. Structure and summarise a body of knowledge relating to a substantial project topic in the area of Data Science
  2. Critically evaluate previous work in the area
  3. Conduct a programme of work in further investigation of issues related to the topic , and discuss and solve conceptual problems which arise during the investigation
  4. Justify design decisions made during the investigation , and critically evaluate the investigation
  5. Present their work, with demonstration of working artifacts where appropriate
Reading List
Project dependent.
Additional Information
Course URL
Graduate Attributes and Skills Not entered
KeywordsNot entered
Course organiserDr Adam Lopez
Tel: (0131 6)50 4430
Course secretaryMrs Sam Stewart
Tel: (0131 6)51 3266
Help & Information
Search DPTs and Courses
Degree Programmes
Browse DPTs
Humanities and Social Science
Science and Engineering
Medicine and Veterinary Medicine
Other Information
Combined Course Timetable
Important Information