Course in Artificial Intelligence for Energy Systems – Ed.2
🎓 Politecnico di Milano · 📍 Milano
Overview
The Course in Artificial Intelligence for Energy Systems, second edition, at the Polytechnic University of Milan is a 40-hour advanced training course, held in person in Milan and in English. It is divided into compulsory and optional modules: foundations of artificial intelligence and practical implementations with the Python Data Science Stack, with in-depth study of thermal modelling, renewable source forecasting, HVAC and electric mobility. It includes exercises and case studies.
It is aimed at data scientists, engineers, asset and energy managers and researchers. Lessons are shown as having started on May 4, 2026. The course is suited to those who work with data and energy systems.
Key features
Admissions
The course is aimed at data scientists, engineers, asset and energy managers and researchers. Technical foundations consistent with the topics covered and good knowledge of English, the language of instruction, are required. The page does not indicate the number of places or the cost, which should be checked in the call for applications of the Polytechnic University of Milan.
The enrolment deadline is given as April 21, 2026, with lessons starting on May 4, 2026: the edition has therefore already started and it is worth asking about later editions. The programme, of 40 hours, is held in person in Milan. Credits and assessment methods are not indicated.
Curriculum
The course offers practical skills in artificial intelligence algorithms applicable to energy systems, with reference to modelling, predictive management, control, optimisation and risk assessment. The programme is divided into compulsory and optional modules. The first module presents the foundations of artificial intelligence; the second is dedicated to practical implementations using the Python Data Science Stack. The optional modules explore specific applications in the energy sectors, such as thermal modelling, renewable source forecasting, HVAC systems and electric mobility. The use of Python, the most widespread language in data science, makes it possible to immediately apply the techniques learned to real data, from consumption time series to forecasts of renewable production.
Teaching comprises 40 hours in total and includes practical exercises and case studies, so as to consolidate knowledge through direct experience of data analysis tools. The course is held in person in Milan and is delivered in English, with the chance to engage with faculty and participants from different backgrounds. It is an advanced training course and not a master's degree or an academic master. The page gives April 21, 2026 as the enrolment deadline and May 4, 2026 as the start of lessons. The hours per module, internship, credits, assessments and price are not specified. The choice of optional modules makes it possible to customise the programme according to one's own application area and to explore in depth the techniques most relevant to one's daily work. The optional modules make it possible to focus on the area of interest, such as thermal modelling of buildings, HVAC systems or electric mobility management, while maintaining a common base of knowledge.
The aim is to provide practical skills in artificial intelligence algorithms in the energy field, with career opportunities in industry and research. The course is aimed at data scientists, engineers, asset and energy managers and researchers who wish to apply artificial intelligence to the management and optimisation of energy systems, in a context where the integration of renewable sources, the electrification of consumption and the availability of large amounts of data require advanced forecasting, control and decision-support tools. The skills acquired are useful for those who wish to apply artificial intelligence to improve the efficiency, reliability and sustainability of energy systems, including in research projects. The course also encourages discussion with colleagues from different sectors and the exchange of experiences on real energy data analysis problems.
Info and enrolment
- Politecnico di Milano
- 📍 Milano
- ✉️ pecateneo@cert.polimi.it
- 🌐 polimi.it
The information provided may be subject to change. For up-to-date information, we recommend contacting the institution directly.
