By Inge de Waard, PhD
Europe’s Green Deal is moving forward with clear goals to make the EU more resource-efficient and competitive. More recently, the European Commission launched the Clean Industrial Deal, a plan to boost competitiveness by turning decarbonisation into a driver of growth for European industry. In today’s political and economic climate, the focus on European competitiveness feels more important than ever. There is, however, still work to do in developing the right skills to meet these goals. Many energy organisations need people who understand energy systems and can also work with data and AI, while handling governance, ethics, security, and real-world deployment. AI4GreenDeal was set up to help bridge this gap.
AI and data as the backbone
The Master’s in Advanced Energy Systems and AI builds on a strong foundation in AI and data, combining technical learning with real datasets from partners and enterprise tools. It also focuses on the reasons behind decisions, including governance and ethics. The aim is to prepare graduates to work effectively in energy organisations, from early prototypes to full production.
Technical courses include skills for delivering projects with an entrepreneurial mindset. Teaching covers topics like peak shaving, energy optimisation, maintenance prediction, and risk and compliance. This approach helps students see both opportunities and real-world challenges to adoption.
Core AI and Data domains
Several key parts of the programme support this foundation. Core areas include AI, data analytics, cloud computing, cybersecurity, IoT, and machine learning, all tailored for energy and transport. Here, students learn practical, useful approaches rather than purely theoretical methods.
Active, industry co-designed learning
To make data and AI skills real and focused on deployment, they need to be an integral part of how people learn across the programme. We include live industry briefs, challenge kick-offs, site visits, and guest lectures that use real project data and tools.
We are creating multi-year mechanisms to keep students and industry engaged. Methods include co-supervision, regular feedback on student projects, and reviews of deployment potential. We believe that ongoing involvement with alumni also raises standards (our ‘Road to C-suite‘ journey within InnoEnergy’s Masters+ programme is a great example).
Pathways and professional upskilling
The double-degree Master’s programme in Advanced Energy Systems and AI, and the modular certifications in AI and data for sustainable energy, offer specialisation pathways in the second year and clear learning outcomes. These are aligned with the energy AI and data skills map and reviewed regularly with partners. In addition to the degree, a stackable module lets companies funnel staff into focused AI/DS training without full degree commitment.
Internships and industry-linked theses give students real experience with production challenges and working with stakeholders. Applied modules use partner data so students can practice how data and model accuracy affect market awareness, prediction quality, scalability, adoption, and compliance.
Quality assurance and inclusivity
By leveraging AI4GreenDeal as an EU co-funded programme, we are addressing one of the most pressing talent challenges in Europe: building job-ready capability at the intersection of digital (including AI and data) and clean energy, while creating a sustainable solution rather than a one-off intervention. We attract diverse talent through scholarships, fee waivers, and mobility budgets, and maintain a pipeline beyond initial funding. These scholarships are supported through industry partnerships, European Commission and HaDEA funding, and the InnoEnergy endowment fund.
If we want AI and data skills to speed up the energy transition, we must be clear about what ‘job-ready’ really means. This requires designing learning experiences around real challenges, such as imperfect data, operational pressure, regulations, cybersecurity needs, and the trade-offs involved in deployment decisions. This is where a twin transition comes into play. Europe’s net-zero and clean-energy transition are increasingly intertwined. Clean energy needs digital capability to scale. And in turn, digital growth is far easier to sustain when energy is clean, affordable and secure.
Inge de Waard, PhD, leads AI and Learning at InnoEnergy. She is an award-winning EdTech pioneer in areas like mLearning, MOOCs, and learning analytics. Inge has driven educational innovation for adult professionals in both formal and informal settings, including low-resource environments worldwide. Her work bridges academic rigour and corporate learning, always focusing on quality, creativity for change, and a strong commitment to diversity and inclusion.
AI4GreenDeal is co-funded by the European Union under the DIGITAL programme, supporting Europe’s strategic priorities in advanced digital education, innovation and the green transition.