Course summary
Sustainability depends on areas such as energy production and environmental management, making it a complex problem. Energy supply is fundamentally important to our homes and workplaces. Future energy supply has to be affordable, stable and secure. Ecosystem management needs to account for the food, water and energy nexus and socio-political context. Digital transformation is an emerging discipline using powerful digital tools and various digital models to solve and manage the increasingly complex problems related to sustainability energy systems. Within this discipline, digital tools and models (such as Artificial Intelligence) are used to analyse data from different energy systems and sources and drive new control and operational strategies and business models, whilst supporting key objectives such as reaching Net Zero emissions. Who is it for? This course is suitable for engineering, computer science, mathematics, environmental, energy and information technology graduates wishing to pursue a technical management career in the rapidly growing area of digital transformation for sustainability. It develops professional engineers, scientists and practitioners with the multidisciplinary skills and ability to analyse current and future sustainability challenges across private and public sectors. Why this course? Countries transitioning to net-zero face a number of challenges in different sectors of their economies. In the core of this transition, affordable and secure energy supply, sustainable development, and the digital transitions aggravate these challenges for organisations to support the government towards net-zero. You will benefit from dedicated state-of-the-art facilities including unique engineering-scale facilities for the development of efficient technologies with low CO2 emissions. In addition to management, communication, teamwork and research skills, each student will attain at least the following learning outcomes from this degree course:
- Design appropriate methods for data acquisition and processing,
- Develop AI algorithms to create data-driven solutions, driving sustainability within organisations,
- Apply Data Science principles through simulation platforms and programming languages to sustainability problems.
Assessment method
Taught Modules 40%, Group Project 20%, Individual Research Project 40%
How to apply
International applicants
Cranfield University welcomes applications from students from all over the world for our postgraduate programmes.
Entry requirements
A first or second class UK Honours degree (or equivalent) in a related science or engineering discipline. Other recognised professional qualifications or several years relevant industrial experience may be accepted as equivalent; subject to approval by the Course Director. Applicants who do not fulfil the standard entry requirements can apply for the Pre-master's course, successful completion of which will qualify them for entry to this course for a second year of study.
Fees and funding
Tuition fees
No fee information has been provided for this course
Tuition fee status depends on a number of criteria and varies according to where in the UK you will study. For further guidance on the criteria for home or overseas tuition fees, please refer to the UKCISA website .
Additional fee information
UK: £11,895
International: £25,955
Provider information
Cranfield University
Cranfield
Bedford
MK43 0AL