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CSC8638 : Diploma Project and Dissertation in Data Science (Inactive)

  • Inactive for Year: 2024/25
  • Module Leader(s): Dr Alma Cantu
  • Owning School: Computing
  • Teaching Location: Newcastle City Campus

Your programme is made up of credits, the total differs on programme to programme.

Semester 2 Credit Value: 20
ECTS Credits: 10.0
European Credit Transfer System


The individual project is a substantial piece of independent work involving the technical and research skills developed in the taught part of the degree. You will have the opportunity to contribute directly to research or development activities, develop your own specialist expertise in the project topic, and further improve your planning and communication skills. You will work closely with one of the School's research groups, and you may also be working with an industrial partner.

Specifically, the module aims to equip students with the following knowledge and skills:
•       To deepen the knowledge and skills acquired in the programme through practice
•       To develop an awareness of the range and limitations of technologies available
•       To enhance research skills and awareness of the professional literature
•       To develop an awareness of the open problems in Data Science

Outline Of Syllabus

Students will either select a project from a list offered by potential supervisors or propose and refine a project proposal with an academic supervisor. Projects will involve learning about some unfamiliar aspect of Data Science. In every project there will be a research component and a strong design, programming and/or analytic element.

1.       Project Definition and Planning:
a.       Bounding and clarifying a problem for research.
b.       Background research; identifying and critically analysing relevant literature and information sources.
c.       Decomposing a problem and forming a project outline in terms of goals and criteria for success. Identifying resources and tooling required.
2.       Supervision: Each project has a lead supervisor and second supervisor, both staff from the School. Additional supervision support may be provided by an industrial partner. The student and lead supervisor will meet regularly throughout the period of the project.
3.       Research: Background research will be undertaken in the selected topic using the skills developed in earlier modules with access to the library and online resources. The supervisor will advise on quality of sources and standards in the topic area.
4.       Development and Analytic Skills: The core of the project will involve carrying out the project plan largely independently, but with guidance from the supervisors.
5.       Dissertation: A dissertation will be prepared, describing the technical background, the work undertaken, the analysis of results and directions for further work. Guidance on the style and content of an academic dissertation will be provided by means of lectures and through the supervisor.

Teaching Methods

Teaching Activities
Category Activity Number Length Student Hours Comment
Guided Independent StudyAssessment preparation and completion31:003:00Ethics form
Guided Independent StudyAssessment preparation and completion10:300:30Oral Examination
Guided Independent StudyAssessment preparation and completion50:302:30Preparation for Oral Examination
Scheduled Learning And Teaching ActivitiesLecture21:002:00Lectures present in person
Guided Independent StudyAssessment preparation and completion601:0060:00Dissertation writing
Guided Independent StudyProject work1141:00114:00technical project work
Scheduled Learning And Teaching ActivitiesDissertation/project related supervision41:004:00Individual supervisor meetings PIP or synchronous online
Guided Independent StudyIndependent study141:0014:00Background Research
Jointly Taught With
Code Title
CSC8639Project and Dissertation in Data Science
Teaching Rationale And Relationship

The project is undertaken with a lead academic supervisor, working in association with one of the research groups of the School or with a collaborating industrial research laboratory (in which case it will be supervised jointly). There will be a designated second academic supervisor to offer additional assistance.

Assessment Methods

The format of resits will be determined by the Board of Examiners

Other Assessment
Description Semester When Set Percentage Comment
Dissertation2M100Word count: up to 10,000 words
Zero Weighted Pass/Fail Assessments
Description When Set Comment
Prof skill assessmntMEthics Form
Oral ExaminationMA structured discussion including a demonstration of the software artefact and a reflection on the key areas of personal development
Assessment Rationale And Relationship

The dissertation provides for an assessment of professional skills in research and development, analysis, and detailed technical communication.

Reading Lists