Timetable information in the Course Catalogue may be subject to change.

University Homepage
DRPS Homepage
DRPS Search
DRPS Contact
DRPS : Course Catalogue : School of Informatics : EPCC on-campus

Postgraduate Course: Dissertation (HPC with Data Science) (EPCC11016)

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 Credits60 ECTS Credits30
SummaryThe dissertation comprises a significant report of describing an MSc-level project undertaken which applies practical HPC and Data Science skills and knowledge developed from the taught courses on MSc in High Performance Computing with Data Science. Students are also required to present their work to the department and their peers and make approprate records of work undertaken and results obtained via use of repository tools (usually Git).

The dissertation must be based on original work carried out solely by the candidate and conform to the University's regulations. The project work may be undertaken within the University or in an external organisation with an appropriate focus. The subject area covered by the project can, with the approval of the Programme Director, be chosen by the student to align with their own research interests as long as it meets the requirements of the programme and course.
Course description To a great extent this will depend on the specifics of the project selected by the student.

Research-level work in HPC and/or Data Science, to include:
- Critically review previous work in the area.
- Plan and implement a programme of work to investigate the topic.
- Analyse the results in the context of previous work.
- Present the work in the form of a written dissertation.
- Summarise the work in an oral presentation to an academic audience.
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Co-requisites
Prohibited Combinations Other requirements None
Course Delivery Information
Academic year 2024/25, Not available to visiting students (SS1) Quota:  84
Course Start Block 5 (Sem 2) and beyond
Timetable Timetable
Learning and Teaching activities (Further Info) Total Hours: 600 ( Dissertation/Project Supervision Hours 12, Summative Assessment Hours 1, Programme Level Learning and Teaching Hours 12, Directed Learning and Independent Learning Hours 575 )
Assessment (Further Info) Written Exam 0 %, Coursework 100 %, Practical Exam 0 %
Additional Information (Assessment) Coursework: 100%, comprising:
Project Performance
Feedback Provided through interaction with supervisor and on assessed work.
No Exam Information
Learning Outcomes
On completion of this course, the student will be able to:
  1. Demonstrate organisation and execution of a reproducible research project
  2. Show understanding of relevant background material and the field more broadly
  3. Analyse and evaluate results obtained and demonstrate their implications within wider area
  4. Design and implement relevant analytical and programmatic techniques relevant to the dissertation topic
  5. Present outcomes and impact of project through both written report and oral presentation to a mixed audience of lay persons and specialists
Reading List
Dependent on project. Input provided by supervisor, but primarily self-sourced by student.
Additional Information
Graduate Attributes and Skills Effective written and diagrammatic communication.
Reflection on learning and practice.
Adaptation to circumstances.
Solution Exploration, Evaluation and Prioritisation.
Special Arrangements Only available to students on the MSc in High Performance Computing with Data Science
KeywordsDissertation,HPC,High Performance Computing,Data Science,Industrial Project,Research Project
Course organiserDr Anna Roubickova
Course secretaryMr James Richards
Tel: 90131 6)51 3578
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