Overview

Lead the future of renewable energy and AI

The online, MSc Renewable Energy and AI combines expertise in renewable energy systems with AI and data science, two of the most in-demand skills worldwide. Get ahead of the curve and learn. Bridging engineering, data science, and responsible innovation, this programme provides you with the skills needed to design and manage resilient, low-carbon infrastructures. You will learn to apply AI and analytics to renewable integration, clean electrification, and energy transition challenges through virtual laboratories, applied industry projects, and independent research.

Created in collaboration with industry and aligned with global sustainability goals, our Renewable Energy and AI master’s degree equips graduates with both the technical expertise and professional agility required to drive real-world change across the evolving renewable energy landscape. If you aren’t ready to commit to a full MSc, there is a Postgraduate Certificate and Postgraduate Diploma award, which you can upgrade to the MSc in the future.

About this degree

Programme details

The MSc Renewable Energy and AI is designed for graduates in engineering, science, or related fields who want to lead in the global clean energy transition. Throughout the programme, you’ll explore how renewable energy technologies combine with artificial intelligence, data analytics, and sustainability-focused engineering. You’ll develop expertise in solar, wind, storage, and clean electrification systems, along with the advanced digital tools and ethical frameworks shaping the future of energy infrastructure. The MSc aligns with Level 2 competence, enabling you to develop practical proficiency in applying and interpreting AI tools, algorithms, and data-driven workflows within the renewable energy domain.

Innovative teaching

Through virtual labs, applied projects, and independent research, you’ll build technical depth, critical thinking, and digital fluency. This hands-on learning approach equips you to innovate, collaborate, and make a meaningful impact across the rapidly evolving renewable and intelligent systems landscape.

Structure

Module delivery structure

This is a part-time programme, offered at three qualification levels, as a full MSc (2 years), PG Diploma (18 months) and a PG Certificate (1 year). Get in touch with our enquiries team if you would like more information on these levels of study.

The programme will be delivered online through live peer engagement sessions, guided study and activities, plus independent learning and reading.

MSc route

The MSc Renewable Energy and AI route is 180 credits:

You will study all modules including the work-based project or research dissertation.

Year 1

Renewable Energy and Sustainable Power Systems

Explore how renewable energy systems drive global decarbonisation. Study solar PV, wind, hydro, and bioenergy – their design, performance, and grid integration – and learn to evaluate data-driven, sustainable power solutions for a resilient and sustainable energy infrastructure. 

Data, AI and Ethics for Sustainable Energy Engineering

Examine how AI, ethical frameworks and data science shape sustainable energy engineering. You’ll apply AI techniques (e.g., neural networks, optimisation, and intelligent control) to renewable energy systems while learning the ethics of digitalisation and the responsible use of intelligent solutions in the global drive for net zero.

Clean Electrification: Renewables, Storage, EVs and Hydrogen

Explore how clean electrification can achieve net zero targets. You’ll study renewable generation, storage, electric vehicles (EVs), and hydrogen systems – learning to integrate these technologies through digital labs, simulation platforms, and real-world cases to design reliable, decarbonised power systems. 

AI-Driven Decision Systems for Energy Planning

Learn to make clean-energy planning decisions with AI-driven tools. You’ll apply optimisation frameworks and advanced modelling techniques to achieve strategic decision-making – balancing technical, economic, and societal trade-offs. Evaluate competing transition pathways, manage risk, and justify evidence-based strategies for resilient and sustainable energy futures.

Year 2

Systems Thinking and Infrastructure for the Renewable Transition

Discover how systems thinking drives the renewable energy transition. You’ll model energy systems, explore digital twins, and assess infrastructure resilience – learning to balance technical, social, and environmental factors to design pathways to achieve net zero. 

Engineering Resilience in System Design

Explore how to engineer resilience and sustainability into renewable systems. You’ll use lifecycle and techno-economic analyses to assess uncertainty, risk, long-term performance. Design adaptive, cost-effective solutions for a future-ready energy infrastructure.

Independent Research Project

Embark on an independent research project that showcases your expertise on renewable energy, AI, or both. Draw upon your acquired academic knowledge to offer a theoretical position on a specific topic, applying theory, research methods, and analysis to produce original, evidence-based insights.

PGDip route

The PG Diploma Renewable Energy and AI route is 120 credits:

You will study Renewable Energy and Sustainable Power Systems, Data, AI and Ethics for Sustainable Energy Engineering, Clean Electrification: Renewables, Storage, EVs and Hydrogen, AI-Driven Decision Systems for Energy Planning, Systems Thinking and Infrastructure for the Renewable Transition Systems Thinking and Infrastructure for the Renewable Transition and Engineering Resilience in System Design.

Year 1

Renewable Energy and Sustainable Power Systems

Explore how renewable energy systems drive global decarbonisation. Study solar PV, wind, hydro, and bioenergy – their design, performance, and grid integration – and learn to evaluate data-driven, sustainable power solutions for a resilient and sustainable energy infrastructure. 

Data, AI and Ethics for Sustainable Energy Engineering

Examine how AI, ethical frameworks and data science shape sustainable energy engineering. You’ll apply AI techniques (e.g., neural networks, optimisation, and intelligent control) to renewable energy systems while learning the ethics of digitalisation and the responsible use of intelligent solutions in the global drive for net zero.

Clean Electrification: Renewables, Storage, EVs and Hydrogen

Explore how clean electrification can achieve net zero targets. You’ll study renewable generation, storage, electric vehicles (EVs), and hydrogen systems – learning to integrate these technologies through digital labs, simulation platforms, and real-world cases to design reliable, decarbonised power systems. 

AI-Driven Decision Systems for Energy Planning

Learn to make clean-energy planning decisions with AI-driven tools. You’ll apply optimisation frameworks and advanced modelling techniques to achieve strategic decision-making – balancing technical, economic, and societal trade-offs. Evaluate competing transition pathways, manage risk, and justify evidence-based strategies for resilient and sustainable energy futures.

Year 2

Systems Thinking and Infrastructure for the Renewable Transition

Discover how systems thinking drives the renewable energy transition. You’ll model energy systems, explore digital twins, and assess infrastructure resilience – learning to balance technical, social, and environmental factors to design pathways to achieve net zero. 

Engineering Resilience in System Design

Explore how to engineer resilience and sustainability into renewable systems. You’ll use lifecycle and techno-economic analyses to assess uncertainty, risk, long-term performance. Design adaptive, cost-effective solutions for a future-ready energy infrastructure.

PGCert route

The PG Certificate Renewable Energy and AI route is 60 credits:

You will study Renewable Energy and Sustainable Power Systems, Data, AI and Ethics for Sustainable Energy Engineering, and Clean Electrification: Renewables, Storage, EVs and Hydrogen.

Year 1

Renewable Energy and Sustainable Power Systems

Explore how renewable energy systems drive global decarbonisation. Study solar PV, wind, hydro, and bioenergy – their design, performance, and grid integration – and learn to evaluate data-driven, sustainable power solutions for a resilient and sustainable energy infrastructure. 

Data, AI and Ethics for Sustainable Energy Engineering

Examine how AI, ethical frameworks and data science shape sustainable energy engineering. You’ll apply AI techniques (e.g., neural networks, optimisation, and intelligent control) to renewable energy systems while learning the ethics of digitalisation and the responsible use of intelligent solutions in the global drive for net zero.

Clean Electrification: Renewables, Storage, EVs and Hydrogen

Explore how clean electrification can achieve net zero targets. You’ll study renewable generation, storage, electric vehicles (EVs), and hydrogen systems – learning to integrate these technologies through digital labs, simulation platforms, and real-world cases to design reliable, decarbonised power systems. 

Online learning

The future of study

Flexible study

Balance your study, work and home commitments, all while working towards your career goals

e-Library access

Full access to a comprehensive and valuable e-library with a wealth of resources to support your studies

Interactive

Study using a diverse range of interactive, modern and dynamic learning resources

Expert-led

Learning activities that have been designed by University of the Built Environment lecturers and subject matter experts

Stay connected

Learn alongside a diverse community of students from all over the world

Time commitment and study breakdown

You will study two modules per semester, with the exception of the final semester, during which the 60-credit Independent Research Project will be undertaken. The expected time commitment is 15-25 hours per week, depending on the module’s credit size. There is an option to study only one module per semester, where the weekly time commitment will be less – this will need to be arranged with our admissions team.

30

Directed study time (%)

35

Self-directed study time (%)

35

Assessment study time (%)

Careers

Where can it take you?

Graduates of our online master’s degree in Renewable Energy and AI are equipped with the interdisciplinary expertise and digital skills to lead innovation in the fast-changing global energy landscape. The programme prepares students for technical, strategic, and policy-focused roles across renewable energy, digital infrastructure, and sustainability sectors. With advanced capabilities in AI, data analytics, energy system design, and intelligent infrastructure, graduates progress into roles such as energy analyst, AI engineer, sustainability consultant, and net zero planner.

  • Grid operations and smart infrastructure planning
  • Renewable energy system design and engineering (solar PV, wind, storage)
  • Energy data analytics and forecasting (AI, machine learning, digital twins)
  • Clean transport infrastructure (EV charging networks, hydrogen)
  • Energy consultancy and project development
  • Sustainability and decarbonisation strategy teams (public or private sector)
  • Research and development in intelligent energy systems
  • Climate-tech startups and energy AI platforms
  • Digital innovation roles in energy technology companies
Case Studies Slide 2
Online learning is
the future

Find out how it's right for you and your studies.

Applications

Ready to apply?