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DRPS : Course Catalogue : School of Informatics : Informatics

Postgraduate Course: Project Preparation (INFR11173)

Course Outline
SchoolSchool of Informatics CollegeCollege of Science and Engineering
Credit level (Normal year taken)SCQF Level 11 (Postgraduate) AvailabilityNot available to visiting students
SCQF Credits10 ECTS Credits5
SummaryThis course comprises all aspects of the planning for the individual research project and is undertaken by the student in conjunction with the project supervisor(s). The student and supervisor(s) will agree the topic of the project, after which the student will conduct initial reading to refine the scope of the project and to inform the development of a detailed plan for its implementation. The student will deliver awritten report and make an oral presentation that both describe the background to the project and outline the plan for its successful completion.
Course description This course encompasses the selection and preparation phase for a dissertation project in High Performance Computing or High Performance Computing with Data Science. The precise topics covered will vary depending on the individual project selected.

Topics covered:
- Report writing
- Academic misconduct and how to avoid it
- Professional Skills
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Co-requisites
Prohibited Combinations Students MUST NOT also be taking Informatics Research Review (INFR11136) OR Informatics Project Proposal (INFR11147)
Other requirements None
Course Delivery Information
Academic year 2020/21, Not available to visiting students (SS1) Quota:  80
Course Start Full Year
Timetable Timetable
Learning and Teaching activities (Further Info) Total Hours: 100 ( Lecture Hours 10, Summative Assessment Hours 1, Programme Level Learning and Teaching Hours 2, Directed Learning and Independent Learning Hours 87 )
Assessment (Further Info) Written Exam 0 %, Coursework 80 %, Practical Exam 20 %
Additional Information (Assessment) 80% Coursework (70% Report, 10% repository) + 20% Oral Presentation (given after Semester 2 exams)
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. Describe in writing the scope of the topic of their individual research project.
  2. Deliver a written project proposal, to be agreed with the project supervisor(s), which includes a workplan, risk analysis and indications of additional work that can be undertaken if time allows.
  3. Present to a lay audience, including other members of the MSc programme, a description of the project topic and the proposed workplan.
  4. Review and understand relevant material and background to a project.
  5. Understand the importance and practicalities of maintaining a repository to track the development of the project (e.g., code, meeting minutes, etc.)
Reading List
Dependent on project topic, initial list provided on project wiki by individual supervisors1. On completion of this course students should be able to: Describe in writing the scope of the topic of their individual research project.
Additional Information
Graduate Attributes and Skills Effective written and diagrammatic communication.
Reflection on learning and practice.
Solution Exploration, Evaluation and Prioritisation.
Presentation Skills.
Presentation of complex data to varied audience.
Special Arrangements Only available to students on the MSc Programmes in High Performance Computing or High Performance Computing with Data Science.
KeywordsProject Preparation,EPCC,HPC,HPCwDS,Parallelism,Data Science,Professional Skills
Course organiserDr Elena Breitmoser
Tel: (0131 6)50 64 94
Course secretaryMr Ben Morse
Tel: (0131 6)51 3398
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