BSc Data Science

Year 3

(Award available for year: Bachelor of Science)

Learning outcomes

1. Demonstrate professional data curation and governance behaviours, articulate an organisation’s legal obligations, and critically evaluate ethical aspects of working with data.
2. Confidently work with large datasets using big data paradigms such as databases, cloud-technology, or high-performance computing.
3. Apply Deep Learning and AI techniques to advanced applications and critically evaluate ethical implications or challenges.
4. Competently work with advanced mathematical techniques from statistics, modelling, or algebra, or demonstrate the ability to effectively acquire domain knowledge from other disciplines.
5. Critically evaluate inferential arguments from different sources and perform rigorous, robust and reproducible mathematical and computational analyses.
6. Explain, employ and evaluate advanced data science tools and techniques with a view to communicating conclusions, making recommendations to organisational decision makers, effecting change, or having an impact on achieving organisational goals.
7. Critically reflect on the role of data, data science and data scientists in organisational, societal and political contexts.

Skills Learning Outcomes
SLO1. Critically evaluate the key professional competencies that you have developed with reference to job person specifications or professional frameworks and articulate the need and strategy for continued professional development as a reflective life-long learner.
SLO2. Apply and integrate your disciplinary and domain knowledge in order to address multi-disciplinary challenges.
SLO3. Communicate your analysis to a range of stakeholders using appropriate data visualisation and storytelling.
SLO4. Conduct independent research on advanced topics whilst organising and managing your own time effectively, using appropriate sources of information and support, and communicating the conclusions of your critical analysis effectively.

Assessment

The majority of the data science modules will be assessed through a combination of individual and collaborative coursework in a variety of formats. The majority of the mathematics modules will be assessed through a combination of in-person exams and coursework assignments. The form of the coursework will vary from module to module but typically would involve solving sets of problems which may or may not require the use of computer packages or computer programming. Project-based modules will be assessed through written submissions and presentations.