Postgraduate taught 

Data Analytics MSc/PgDip/PgCert: Online distance learning

Data Analytics Project (ODL) STATS5093P

  • Academic Session: 2024-25
  • School: School of Mathematics and Statistics
  • Credits: 60
  • Level: Level 5 (SCQF level 11)
  • Typically Offered: Full Year
  • Available to Visiting Students: No
  • Taught Wholly by Distance Learning: Yes
  • Collaborative Online International Learning: No

Short Description

This course constitutes the dissertation phase of the MSc programmes in Data Analytics (ODL). It gives students with an opportunity to work independently on a data analysis or software development project, showcasing the skills acquired on the MSc programme.

Timetable

None.

Excluded Courses

Data Analytics Professional Portfolio (ODL)

Assessment

20% presentation and mini viva, 80% final submission of a portfolio, which includes a dissertation

Course Aims

This course aims to provide students with an opportunity to practice their data-analytic skills acquired on the programme. It is intended that most project focus on the analysis of a complex real-world data set using advanced data analytic methods and/or on the development of software to carry out complex data-analytic tasks. The course also aims to train students in discussing their work with others, presenting it to an audience and synthesising conclusions in a report.

Intended Learning Outcomes of Course

By the end of this course students will be able to: 

1. design and execute a project plan for an appropriate data analysis or software development project;
2. investigate and discuss the merits and risks involved in the approach taken as well as other strategies that could have been employed;

3. integrate and consolidate the knowledge and skills they have gained from other components of their degree programme;
4. implement and/or use both standard and advanced data analytic methods in a real-world context;

5. critically reflect upon their work discussing assumptions and limitations;

6. present key results and conclusions to both technical and non-technical
 audiences; and
7. document their work and synthesise and write up results and conclusions in a concise report and executive summary.

Minimum Requirement for Award of Credits

Students must submit at least 75% by weight of the components (including examinations) of the course's summative assessment.