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    Taught postgraduate

    PgC / PgD / MSc Data Science for Global Agriculture, Food and Environment

    Key information

    Year of entry

    Duration

    1 year (full-time) or 2 to 3years (part-time)

    Start date

    February 2025 or September 2025

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    Course description

    There is a huge skills gap in the UK workforce when it comes to data science and artificial intelligence. The Government’s Digital Skills strategy estimates that within the next 20 years, 90 percent of all jobs will require some element of digital skills, with data science pinpointed as a priority area.

    At the same time, the agriculture, food and environment sectors are experiencing a radical shift in demand for data scientists, thanks to applications in agri-tech, and smart farming and a large surge in demand for general skills using big data and open data across the sector through 2030. At the same time, there is a huge demand for data-driven solutions for best-practice solutions for conservation and environmental issues that are compatible with the future of farming. This new course, the first and only of its kind in the UK, seeks to address these challenges.

    Our flexible programme consists of core training in data science tools and further specialised training so that you can choose your own path: 鈥痟elp agri-food companies make smarter business decisions or use data to solve important conservation challenges. 

    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 Masters in Data Science course is ideal for candidates with a background in agriculture, food science, in wildlife, conservation and environmental science, or for someone from a data science background who wishes to enter one of these subject areas. 

     For domestic UK students, this course offers a significant opportunity to acquire advanced skills in data science - identified by the UK government as critical for future economic growth and innovation. 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 strategic initiatives in data skills, 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 skills 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. 

    How is the course structured?

    Both Data Science courses commence with a suite of online modules, which can be completed to achieve a Postgraduate Certificate (PgC). As you progress to Postgraduate Diploma (PgD) and then Masters (MSc) level, you will complete modules aligned your field of interest. Please see the full course structure 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 in 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 CV. 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

    This course is ideal for students with a background in agriculture who are interested in pursuing a career in data science or for students with a background in computing or maths interested in pursuing a career in data science in the agriculture and food industries. 

    Candidates should possess one of the following: 

    1. An honours degree in agriculture, environmental science, or a related scientific subject. 
    1. A good UK-based Higher National Diploma or Foundation Degree or equivalent in agriculture, environmental science, or related scientific subject together with related industrial or professional experience of at least two years. 
    1. A Graduate Diploma, Graduate Certificate 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. 

     

     

    "The agri-food sector is seeing a radical shift in demand for data scientists, thanks to applications in agri-tech, and smart farming and a large surge in demand for general skills using big data and open data across the sector."

    Edwin Harris

    Entry requirements for 2025

    This course is ideal for students with a background in agriculture who are interested in pursuing a career in data science or for students with a background in computing or maths interested in pursuing a career in data science in the agriculture and food industries.

    Candidates should possess one of the following:

      1. An honours degree in agriculture, environmental science, or a related scientific subject.
      2. A good UK-based Higher National Diploma or Foundation Degree or equivalent in agriculture, environmental science, or related scientific subject together with related industrial or professional experience of at least two years.
      3. A Graduate Diploma, Graduate Certificate 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.

    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

    Teaching and learning

    Each module will be delivered by block delivery over a five-day period. All PgC modules will be delivered online only. 

    Whilst away from Harper Adams, students will be supported via the VLE as indicated in the module descriptors and will have access to teaching staff via telephone and email.

    The curriculum is designed to meet the requirements of two types of potential students who wish to work as data scientists within the agriculture and food-related industries.

    The first group are individuals who have an undergraduate or technical background in some aspect of data science and are looking to obtain the necessary agriculture and food experience and the second group are individuals who have a background in agriculture and/or food and wish to undertake training in data science.

    Both types of students will be supported by an Agriculture for the Land & Business Professional Boot Camp or a Data Science Boot Camp whereby students undertake a non-credit bearing training course to directly support their introduction to study.

    The data science component of the course will be supported by a range of online materials.

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