The Centre for Agriculture Data Science (AgriDat) brings together experts in Agriculture Data Science, acting as a focal point for a team of multidisciplinary researchers. Drawing from statistics and computer science within applications subject areas including agronomy, animal science, and ecology, this centre is dedicated to utilizing best practice in experimental design and data acquisition.
We build solutions using artificial intelligence and machine learning to address pressing issues in food production, agriculture, and environmental sustainability.
By transforming data into actionable insights, AgriDat aims to advance scientific understanding and provide accessible data-driven solutions for farmers, policy makers, and industry stakeholders, contributing to the enhancement of global food security and environmental stewardship. AgriDat has a strategic role in building data-centric research capacity and practice across the university and beyond.
Research contact 01952 81 5113
Monday to Friday: 9am - 5pm
Our team excels in leveraging advanced AI, machine learning, and experimental design to address challenges in food production and environmental sustainability. With a focus on experimental design and data acquisition, we transform data into actionable insights tailored for farmers, policy makers, and industry leaders. We are committed to building capacity with our partners and stakeholders to make advances in artificial intelligence and statistical knowledge available to a wide group of stakeholders and challenges. Because of this, we have a pivotal role in expanding data-centric research across the agriculture and environment sectors, leveraging our strategic expertise in these fields. For partners and collaborators, AgriDat represents an opportunity to partner with data experts committed to global food security and environmental conservation.
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Staff in the Centre for Agriculture Data Science (AgriDat) carry out research in applied data science, including statistical design, computer vision, remote sensing, and artificial intelligence, applied to problems in agriculture, agri-tech, and wildlife monitoring. Examples of current and past projects can be found in our project and 91茄子ations listings. Our strength is in facilitating data-driven solutions in cutting edge machine learning and statistical design for our partners and collaborators.
If you would like to discuss how we can support your project or enterprise, please contact us.
Specializing in knowledge creation through data, we provide a tailored consulting service for partners who require statistical support and technical advice in implementing artificial intelligence and agri-tech solutions. Advice is available for all aspects of methodology and a range of application from data analysis, the design of data collection and data pipelines, decision support systems, and computer vision and edge computing. We can provide guidance for teams needing to communicate complex results to a range of policy makers and practitioners, for example through technical analysis reports. Teams can potentially benefit most from our support if we consult at the data collection design stage. Please contact us to discuss your requirements.
AgriDat supports tailored training courses for all aspects of data science and statistics, including technical training in data analysis (for example, using R and Python), specific techniques (for example, machine learning, deep learning), or specific applications (data dashboards, computer vision, large language models). Training can be tailored to suit the skill level of participants and other specific requirements. Our staff are extremely experienced in technical data science training and have delivered short courses for business and research in the UK and internationally for over 20 years. If you are interested in training tailored to your requirements, please contact us to discuss this further.
Placements are available if you are interested in shadowing AgriDat staff working on real-world applied data science problems. This can help you understand what implementing data-driven solutions involves, while enabling you to gain experience on a specific stage of implementation, for example, experimental design prior to data collection, implementing a data pipeline in the cloud, designing the communication of analysis results, working with both technical and non-technical stakeholders, or designing a solution with artificial intelligence from data to output. You may also choose to bring your own data or project to work on and develop along with the support of AgriDat staff. Placement availability will depend on Centre activities so please contact us to discuss the opportunities further.
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