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).
- School
- School of Biosystems and Food Engineering
- Attendance
- Full Time
- Level
- Graduate Taught
- NFQ Level
- 9
- Award
- Master of Science
- Mode of Delivery
- Blended
- Programme Director
- Dr Dimitrios Argyropoulos
- Overall Programme Credits:
- 90
- Programme Credits:
- Stage 1
Core/Option: 90 Electives: 0 - Major/Minor Core & Option Credits:
- Stage 1: 90
Curricular information is subject to change.
Digital Technology for Sustainable Agriculture is the integration of new and advanced technologies into crop and livestock farming systems to enable farmers and other professionals in the sector to improve food production.
UCD’s MSc Programme on Digital Technology for Sustainable Agriculture is targeted towards providing students with cutting edge training in digital technology areas that include a number of modules in computer programming, data processing, Internet-of-Things and machine learning implementations.
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.
Module Information:
Under the "What modules can I take?" section below you will see general module information, for a more detailed description including module selection rules click here.
Graduates of the MSc Digital Agriculture may find employment opportunities in the following areas:
- Agricultural machinery (e.g. Agco, CNH Industrial, Claas, John Deere)
- Precision farming (e.g. Amazone, Lemken, Rauch, Dairymaster)
- Decision support in agriculture (e.g. Corteva Digital Ag, Syngenta Global)
- IoT, data and predictive analytics (e.g. BASF, Bosch, IBM, Microsoft)
Stage 1
T385 Digital Technology for Sustainable Agriculture (Sept) is a 1-year 90-credit full-time Masters Programme comprising 30 Core credits per trimester to ensure a balanced workload. The 30-credit module BSEN40090 Biosystems Engineering Thesis is a Core Module and must be taken by all students in the Summer Trimester.
Below is a list of all modules offered for this degree in the current academic year. Click on the module to discover what you will learn in the module, how you will learn and assessment feedback profile amongst other information.
Incoming Stage 1 undergraduates can usually select an Elective in the Spring Trimester. Most continuing undergraduate students can select up to two Elective modules (10 Credits) per stage. There is also the possibility to take up to 10 extra Elective credits.
| Trimester | Credits | |||
|---|---|---|---|---|
Stage 1 Core Modules |
BSEN40500 | Hyperspectral imaging | Autumn | 5 |
Stage 1 Core Modules |
BSEN40740 | Soil Technology | Autumn | 5 |
Stage 1 Core Modules |
BSEN40760 | Computers & Electronics in Ag | Autumn | 5 |
Stage 1 Core Modules |
BSEN40770 | Advances in Crop Mechanisation | Autumn | 5 |
Stage 1 Core Modules |
BSEN40780 | Remote Sensing and GIS | Autumn | 5 |
Stage 1 Core Modules |
STAT40800 | Data Prog with Python (online) | Autumn | 5 |
Stage 1 Core Modules |
BSEN30210 | Precision Agriculture | Spring | 5 |
Stage 1 Core Modules |
BSEN30520 | Sensors and Sensing Systems | Spring | 5 |
Stage 1 Core Modules |
BSEN30530 | Numerical Methods for Agricult | Spring | 5 |
Stage 1 Core Modules |
BSEN40510 | Precision Livestock Management | Spring | 5 |
Stage 1 Core Modules |
BSEN40520 | Optical Spectroscopy | Spring | 5 |
Stage 1 Core Modules |
BSEN40750 | IoT enabled AgriFood Prod | Spring | 5 |
Stage 1 Core Modules |
BSEN40090 | Thesis | Year-long (12 months) | 30 |
See the UCD Assessment website for further details
Module Weighting Info
Module Weighting Info
| Award | GPA | ||||
|---|---|---|---|---|---|
| Programme | Module Weightings | Rule Description | Description | ||
| MTEMP009 | Stage 1 - 100.00% |
Standard Honours Award | First Class Honours | 3.68 |
4.20 |
| Second Class Honours, Grade 1 | 3.08 |
3.67 |
|||
| Second Class Honours, Grade 2 | 2.48 |
3.07 |
|||
| Pass | 2.00 |
2.47 |
|||
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.