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

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

Different course options

Full time | Harper Adams University | 1 year | SEP-22

Study mode

Full time


1 year

Start date


Key information

Qualification type

MSc - Master of Science

Subject areas

Agriculture (General) Environmental Science Data Science

Course type


Course Summary

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 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.

At the same time, the agri-food sector is 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. This new course, the first and only of its kind in the UK, seeks to address these dual challenges.

This course is ideal for candidates with a background in agriculture, food science, or in wildlife, conservation and environmental science, or for someone from a data science background that wishes to enter one of these subject areas. Our flexible programme consists of core training in data science tools and further specialised training, so that you can choose your own path: help agri-food companies make smarter business decisions, or use data to solve important conservation challenges.

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.

Teaching and learning

Each module will be delivered by block delivery over a five-day period.

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 student 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.

You will gain Intermediate awards: PG Cert, PG Dip.


The primary way to communicate data to both data experts and lay persons is with the use of graphical displays. The overall aim for this module is to provide a practical overview of contemporary techniques and tools for the effective communication of data and stories. The module will provide a practical overview of graphics, graphics systems and analytics techniques using appropriate software platforms (e.g. R, Rstudio, ggplot2, Shiny, Tableau, etc.). The theory and practise of the "grammar of graphics" will be embedded in practical exercises to explore diverse methods of displaying information. The module will involve group practical work under time constraints to simulate real-world graph analytic tasks. The module will culminate with each participant developing a portfolio of graphics to build and develop to showcase skills to prospective employers (e.g. using Github, Shiny, etc.).

Tuition fees

UK fees
Course fees for UK students

For this course (per year)


International fees
Course fees for EU and international students

For this course (per year)


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: An honours degree in an appropriate agricultural, scientific or veterinary subject; A good UK based Higher National Diploma or Foundation Degree or equivalent in an appropriate agricultural or scientific subject together with related industrial or professional experience of at least two years; 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.

University information

Harper Adams University has been providing world-leading, specialist education in the fields of agriculture, farming, and animal science for 120 years. It is now the UK’s market leader, by share*, for postgraduate degrees in agricultural and veterinary subjects. It offers Masters programmes developed in conjunction with industry in a range of topics related to agricultural production, agri-tech, food industry management, global agri-business,...more