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    Taught postgraduate

    PgC / PgD / MSc Data Science for Artificial Intelligence

    Key information

    Year of entry

    Duration

    1 year full-time 2 to 3 years part-time

    Start date

    February 2025 or September 2025

    First intake February 2025

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    Course description

    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 西瓜视频'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. 

     

    Who should study this course? 

    This course is designed for individuals seeking to advance their skills in data science and artificial intelligence, catering to a diverse range of backgrounds. It is suitable for graduates from 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. The programme equips them with the necessary tools and knowledge to integrate advanced data methodologies into their respective sectors.  

    Additionally, graduates with a background in computer science, mathematics, statistics, or related fields will find this course valuable for specialising in data science and AI. It offers practical training in areas like computer vision, cloud computing, and generative AI, including large language models such as ChatGPT, thereby enhancing their existing skill sets and preparing them for specialised roles in the industry. 

    The course is also ideal for professionals aiming to enhance their digital competencies to meet industry demand for data science and AI expertise. It provides a pathway to bridge the skills gap and advance their careers by offering comprehensive training aligned with current technological advancements and industry needs. This will suit individuals interested in professional development in AI and machine learning, AI-driven communication, and data analytics will gain in-depth knowledge and practical experience to meet the need for qualified experts across various sectors. The structured progression from foundational online modules to specialised on-campus studies allows students from various educational backgrounds to build their expertise effectively. 

    For domestic UK students, this course offers a significant opportunity to acquire advanced skills in data science and artificial intelligence—fields identified by the UK government as critical for future economic growth and innovation. With a recognised skills gap in these areas, students can position themselves at the forefront of national efforts to strengthen the country's digital competencies. The programme enables UK students to directly contribute to and benefit from the nation's strategic initiatives in AI and data science, enhancing their career prospects in a rapidly expanding job market while supporting the UK's ambition to remain a global leader in these pivotal industries. 

    International students will find this programme beneficial due to the global surge in demand for data science and AI professionals and the United Kingdom's leadership in these fields. The course offers the opportunity to gain cutting-edge skills and expand career horizons on an international scale, making it an attractive option for those wishing to study in the UK. 

    Whether you are new to data science or looking to deepen your existing knowledge, this course offers a comprehensive route to develop skills aligned with industry demands and technological advancements. It is ideal for those aspiring to become specialists in machine learning and artificial intelligence, providing both the academic foundation and practical experience necessary to excel in these rapidly evolving fields. 


    How is the course structured? 

    Both Data Science courses commence with a suite of core modules, which can be completed (optionally online) to achieve a Postgraduate Certificate (PgC). As you progress to Postgraduate Diploma (PgD) and then Masters (MSc) level, you will complete modules aligned your chosen route. Please see the full course structure - view the full module breakdown below. 
     
    All students begin by studying the Professional Skills for Data Science module followed by the Statistical Analysis for Data Science module. 

    How will I be taught? 

    This programme is taught in English. International students should review our English language requirements.  

    You will study modules with a credit value of 15 (except the Masters Research Project, 60 credits), with 1 credit being equivalent to 10 hours of notional learning time. This will be delivered by direct contact and independent study. Typically, at level 7, the ratio of contact time to independent study is approximately 1:5, which for a 15 credit module, equates to around 30 hours of contact and 120 hours of independent study. This will typically be delivered five day blocks Harper Adams for PgC and PgD, with directed study being supported through the Harper Adams Virtual Learning Environment (The Learning Hub).   

    Teaching methods will include lectures, but there is an emphasis on tutorials and practical hands-on data analysis sessions. 

    How will I be assessed? 

    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.  

    Entry requirements

    Candidates should possess one of the following: 

    1.  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.
    2. 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.
    3. 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. 

    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.

    What will I study?

    Optional modules are indicative and may be subject to change.

    Contacts

    For course related enquiries please contact:

    postgraduate@harper-adams.ac.uk

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