Digital Technology for Sustainable Agriculture

This programme will build student’s knowledge and skills-base to address the complexities of developing, deploying and managing digital technology in the agri-food sector with a focus on enhancing efficiency, sustainability and resilience at all levels of food production.



The programme also offers hands-on experience on a range of novel digital technology, training in state-of-the-art labs and applied research in a real life environment at the Lyons Research Farm.



Delivery Mode & Themes



​This programme is primarily delivered face to face, but will also include some fully online modules and blended delivery models. All modules are optional and students will be able to take themed clusters of modules (e.g. three modules of precision farming, three modules of sensing technology, three modules of computers and electronics, three modules of data science) to reflect specific technical interests or needs for upskilling.



Individual Modules:

For students that are not in a position to take on the full programme a number of the modules on this programme can be taken individually via the Advance Centre catalogue. Most modules are online so that you can fit study around your work and life.



What will I Learn

The MSc programme provides students with an understanding of the “Digital Technology” tools that digitise data capture relating to the environment and activity (sensors circuits, systems and programming), move the data (accumulation networks), store the data (databases), analyse data to gain insights (models and AI), share the resulting information along the agricultural value chain (distribution networks) and provide actors and stakeholders access to the digital chain (interfaces).

Stage 1 Core Modules

BSEN40500 Hyperspectral imaging Autumn 5

BSEN40740 Soil Technology Autumn 5

BSEN40760 Computers & Electronics in Ag Autumn 5

BSEN40780 Remote Sensing and GIS Autumn 5

CPSC40100 Advances in Crop Mechanisation Autumn 5

STAT40800 Data Prog with Python (online) Autumn 5

BSEN30210 Precision Agriculture Spring 5

BSEN30520 Sensors and Sensing Systems Spring 5

BSEN30530 Numerical Methods for Agricult Spring 5

BSEN40510 Precision Livestock Management Spring 5

BSEN40520 Optical Spectroscopy Spring 5

BSEN40750 IoT enabled AgriFood Prod Spring 5

BSEN40090 Thesis Year-long (12 months) 30

Applicants must hold a bachelor’s degree with a minimum upper second-class honours (NFQ level 8) or international equivalent in agriculture, biological science, physical science, environmental related, engineering, computer science or other appropriate discipline.



Where an applicant has no formal qualification encompassing agriculture/biology, practical knowledge of, and experience in, agriculture will be required.



Applicants whose first language is not English must also demonstrate English language proficiency of IELTS 6.5 (no band less than 6.0 in each element), or equivalent.



You may be eligible for Recognition of Prior Learning (RPL), as UCD recognises formal, informal, and/or experiential learning. RPL may be awarded to gain Admission and/or credit exemptions on a programme. Please visit the UCD Registry RPL web page for further information. Any exceptions are also listed on this webpage.

https://tinyurl.com/2ae2ffax

1 year full-time

Delivery: Blended

T385 MSc in Digital Technology for Sustainable Agriculture Master of Science Full-Time

Commencing September 2025

Graduate Taught

Ireland is home to the world’s top 10 technology companies. It is known as the IT Capital of Europe and is among the world’s most technologically developed nations. There are excellent job opportunities, with 5,000 job vacancies in the sector at present. Big Tech companies have recently, to a greater or lesser extent, entered farming and food industries. In addition, a dynamic transformation is taking place in the world of agriculture, triggered by the rapid emergence and growth of AgTech startups. This highlights the immense career possibilities and promising future for our graduates in the areas of precision farming, decision support in agriculture, IoT, smart sensors, intelligent algorithms, data, and predictive analytics.