Data Science for Global Agriculture, Food and Environment

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Organisation
Harper Adams University
Start - End
12 Sep
Study Options
Full Time
Fee
GBP 9250 - 9250
Fee International
GBP 11250 - 11250

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 per cent 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 environment 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.

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.

"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

PgC (60 credits from)

  • Statistical Analysis for Data Science
  • Techniques in Machine Learning and Artificial Intelligence
  • Data Visualisation and Analytics
  • Elective module

PgD (120 credits from)

  • Statistical Analysis for Data Science
  • Techniques in Machine Learning and Artificial Intelligence
  • Data Visualisation and Analytics
  • Elective module
  • Big Data and Decision Making- Case Studies

Optional modules

  • Advanced Research Methods - Applied Econometrics
  • Geographical Information Systems
  • Fundamentals of Agroecology
  • Ecological Entomology
  • Biodiversity and Ecosystem Services
  • Food Security and Sustainability
  • Agri-food Supply Chain Strategy, Operations and Management
  • Agricultural Economics, Policy and Trade
  • Elective module

MSc (180 credits from)

  • Statistical Analysis for Data Science
  • Techniques in Machine Learning and Artificial Intelligence
  • Data Visualisation and Analytics
  • Elective module
  • Big Data and Decision Making- Case Studies
  • Research Project

Optional modules

  • Advanced Research Methods - Applied Econometrics
  • Geographical Information Systems
  • Fundamentals of Agroecology
  • Ecological Entomology
  • Biodiversity and Ecosystem Services
  • Food Security and Sustainability
  • Agri-food Supply Chain Strategy, Operations and Management
  • Agricultural Economics, Policy and Trade
  • Elective module

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.

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