14Jun
UndergraduateCourse summary
Why study Data Science? There is a huge skills gap in the United Kingdom’s workforce when it comes to data science and artificial intelligence. The Government’s Digital Skills strategy states that within the next 20 years, 90 per cent of all jobs will require some element of digital skills, with data science pinpointed as a priority area for investment. Developed off the back of Harper Adams University's existing taught postgraduate programme in Data Science for Global Agriculture, Food and Environment, the new Data Science for Artificial Intelligence PgD and MSc routes add training on a specific set of data science skills involving computer vision, cloud computing and generative Artificial Intelligence (AI), such as large language models (for example, ChatGPT). The UK has positioned itself as a global leader in AI and data science, with government initiatives such as the AI Sector Deal and the National Data Strategy emphasising the importance of these fields. However, despite this focus, there remains a significant skills gap. According to the UK Government 2021 AI Roadmap, the demand for AI and data science professionals far outpaces the supply. The need for experts in machine learning, AI-driven communication, and data analytics is critical, as companies across sectors struggle to find qualified candidates. These skills are also in high demand internationally, so the course will be attractive to international students wishing to study in the UK.
Assessment method
Assessments are designed to result in a finished project that can be used to showcase skills acquired during the course, e.g. as a list of projects suitable for your c.v. Each module typically has one assessment. There is a focus on applied and practical projects, allowing students to apply knowledge and understanding in a more realistic context. The Masters Research Project (MRP) required for the MSc includes submission of a substantial research report. Block-based study: Modules are delivered in one week (and in a select few modules two week) blocks on campus. You will know in advance which weeks require physical attendance as they’ll be scheduled on the timetable. In addition to this, you will be required to allocate time for self-study to complete the assignments associated with each of the modules. Some modules may also include research and/or exam elements, these are also highlighted on the timetable.
Entry requirements
Candidates should possess one of the following: An honours degree in an appropriate subject-specific disciplines such as human health, finance, agriculture, food science, environmental studies, or other specialised fields who wish to apply data science and AI techniques within their areas of expertise, including those with a background in technical subjects like computer science, mathematics, or statistics; A good UK based HND or Foundation Degree or equivalent in a relevant subject together with related industrial or professional experience of at least two years; A Graduate Diploma or Graduate Certificate in a relevant discipline or equivalent. To apply for this course a degree indicating basic quantitative and mathematical skills is required and applicants are expected to demonstrate some ability and interest in this area. Whilst formal techniques are taught as part of the MSc course, some prior training and enthusiasm in these areas is expected.
Fees and funding
Tuition fees
No fee information has been provided for this course
Tuition fee status depends on a number of criteria and varies according to where in the UK you will study. For further guidance on the criteria for home or overseas tuition fees, please refer to the UKCISA website .
Additional fee information
No additional fees or cost information has been supplied for this course, please contact the provider directly.
Provider information
Harper Adams University
Newport
TF10 8NB