Optional placement:
Industrial Placement (120 credits)
Spend 48 weeks on placement working within the industry. Refine, plan, schedule and produce an individual project based on your experience. Critically reflect on the skills and experience gained as part of your placement.
Final year (national level 6)
Computing Project (40 credits)
Articulate an in-depth knowledge and critical understanding of your chosen research topic. Develop your professional skills, such as problem-solving, creativity, critical thinking, self-reflection, and time management. Collect, organise, and present your body of work, including a critical evaluation and correct citation and reference of appropriate research sources.
Artificial Intelligence (20 credits)
Examine a range of AI techniques and their application to problem-solving within society, industry, and research. Develop an awareness of the contemporary developments in the field of AI and their application and potential implications. Critically assess real-world problems and determine which AI approaches are suitable for their solutions.
UX Design (20 credits)
Translate research user and contextual data into human-centered design tools such as user stories, personas, and scenarios. Design and develop digital prototypes for a given problem specification. Critically evaluate the usability and user experience of a given interactive system.
Mobile Technologies (20 credits)
Investigate the different ways apps can be created and look at the range of technologies available for the creation of web apps, hybrid applications, and native applications. Design and create applications for a range of different hardware platforms, such as smartphones, tablets, wearable technology, and embedded systems. Critically evaluate a mobile application designed for cross-platform deployment.
Big Data and Visualisation (20 credits)
Dive into the key concepts and applications of Big Data, including how to manage, use, analyse and visualise Big Data effectively in real-world scenarios. Examine Big Data challenges, including privacy issues and data storage. Select and apply Data Science tools and methods such as data visualisation, data mining, and data analytics for analysing Big Data sets.
