Postgraduate Course: MSc by Research Thesis (Data Science; 120pt) (INFR11107)
|School||School of Informatics
||College||College of Science and Engineering
|Credit level (Normal year taken)||SCQF Level 11 (Postgraduate)
||Availability||Not available to visiting students
|Summary||Students will pursue a year long 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.
For this 120 credit project, the dissertation will normally include a more extensive investigation and critical evaluation of the topic, the use of more advanced methodology, or more time-intensive research methods than in a 90 credit project.
Entry Requirements (not applicable to Visiting Students)
||Other requirements|| For students on the MSc by Research in Data Science only - by special permission.
This course can only be chosen by students with sufficient background in data science to justify partial exemption from the programme's coursework requirements.
Course Delivery Information
|Academic year 2015/16, Not available to visiting students (SS1)
|Learning and Teaching activities (Further Info)
Seminar/Tutorial Hours 10,
Dissertation/Project Supervision Hours 40,
Programme Level Learning and Teaching Hours 24,
Directed Learning and Independent Learning Hours
|Assessment (Further Info)
|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.
|No Exam Information
| 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.
4 - Discuss and solve conceptual problems which arise during the investigation.
5 - Justify design decisions made during the investigation.
6 - Critically evaluate the investigation.
7 - Present their work, with demonstration of working artifacts where appropriate.
|Course organiser||Dr Charles Sutton
Tel: (0131 6)51 5634
|Course secretary||Miss Maree Matheson
Tel: (0131 6)50 9989
© Copyright 2015 The University of Edinburgh - 18 January 2016 4:13 am