Data Science (including foundation year) - BSc (Hons)

Modular structure

The modules listed below are for the academic year 2021/22 and represent the course modules at this time. Modules and module details (including, but not limited to, location and time) are subject to change over time.

Year 0 modules include:

• Cyber Security Fundamentals (core, 30 credits)
• Introduction to Robotics and Internet of Things (core, 30 credits)
• Mathematics (core, 30 credits)
• Programming (core, 30 credits)

Year 1 modules include:

• Data Analysis and Financial Mathematics (core, 30 credits)
• Fundamentals of Computing (core, 15 credits)
• Introduction to Information Systems (core, 15 credits)
• Logic and Mathematical Techniques (core, 30 credits)
• Programming (core, 30 credits)

Year 2 modules include:

• Data Analytics (core, 15 credits)
• Data Engineering (core, 15 credits)
• Data Science for Business (core, 15 credits)
• Databases (core, 15 credits)
• Professional Issues, Ethics and Computer Law (core, 15 credits)
• Programming with Data (core, 15 credits)
• Statistical Methods and Modelling Markets (core, 30 credits)

Year 3 modules include:

• Artificial Intelligence and Machine Learning (core, 15 credits)
• Big Data and Visualisation (core, 15 credits)
• Project (core, 30 credits)
• Academic Independent Study (option, 15 credits)
• Advanced Database Systems Development (option, 30 credits)
• Artificial Intelligence (option, 15 credits)
• Cryptography and Number Theory (option, 15 credits)
• Ethical Hacking (option, 15 credits)
• Financial Modelling and Forecasting (option, 30 credits)
• Formal Specification & Software Implementation (option, 30 credits)
• Work Related Learning II (option, 15 credits)

Assessment

You’ll be provided with opportunities to develop an understanding of good academic practice, as well as the skills necessary to demonstrate this. In particular, you’ll be encouraged to complete weekly tutorial and workshop exercises as well as periodic formative diagnostic tests to enhance your learning. During tutorial and workshop sessions you’ll receive ongoing support and feedback on your work to promote engagement and provide the basis for tackling the summative assessments.

During the foundation year, a continuous assessment approach is taken, which will see you take part in:

• regular online quizzes
• lab-based tests
• short answer tests
• individual and group assignments

This approach allows for diagnostic and other formative assessments to help identify where targeted or individual support may be required.

As the course continues, you’ll be assessed by a variety of methods throughout your studies. Module assessment typically consists of a combination of assessment methods including:

• coursework
• in-class tests
• exams

Coursework can include an artifact such as an output of dataset analysis, application of algorithms, data trends or program code in addition to a written report/essay. The volume, timing and nature of assessment will enable you to demonstrate the extent to which you have achieved the intended learning outcomes.

Formative and summative feedback will be provided using a variety of methods and approaches, such as learning technologies and one to one and group presentations of the submitted work at various points throughout the teaching period.