This course offers a unique opportunity to analyse, forecast, and optimise energy flexibility and demand using data science and artificial intelligence techniques. The course focuses on practical use cases in the energy sector, providing a comprehensive introduction to data science with a hands-on approach. Participants will learn how to use Python and other tools to analyse and visualise energy demand data, as well as how to share their results with other stakeholders using advanced dashboards.
Throughout the course, students will gain practical knowledge of state-of-the-art tools for monitoring and experimenting with energy datasets. They will also explore the limitations of machine learning models and how they rely on time series and statistical principles to forecast energy demand. Participants will learn how to optimize the behavior of energy flexible resources using arbitrary cost functions, tracking their experiments using cutting-edge tools.
Designed based on industry requirements and feedback from hundreds of learners, this course is the fifth iteration of a successful collaboration between EIT InnoEnergy and several leading European partner universities, including KU Leuven, KTH, UPC, and Grenoble INP.
The Data Science & AI for energy engineers course offered in summer 2024 is powered by:
Course dates: 22 July – 02 August 2024
Effort Level: 60 to 80 hours, spread over two weeks. Sessions take place from Monday to Friday from 09.30 – 17.30 CET.
Course costs: 3,950 EUR
Delivery: Hybrid course offered online and face-to-face at KU Leuven. Additional face-to-face sessions at other EIT InnoEnergy partner locations such as KTH Royal Institute of Technology may become available depending on course demand.
Pre-requisites:
Registration: registrations will be opened from 15 March – 15 April 2024.
The final results of the application process will be communicated to applicants in early June 2024.
Financial support:
InnoEnergy MSc and PhD students can apply for a fee waiver and/or a travel grant (up to 500 euros per student) to cover travel and accommodation expenses in Leuven. Grants are awarded based on a motivation statement submitted by students on the application form.
This course on energy data science is designed for EIT InnoEnergy master’s students who wish to learn how to streamline existing workflows and develop new services through data-driven decision making.
The course content is applicable to a wide range of energy careers, including working in energy aggregators, system operators, and utilities.
Students of the Master’s in Energy for Smart Cities obtain 3 ECTS from following this course.
Limited seats are available for early-stage PhD researchers for the summer 2024 edition of the course. Please get in touch with contact.sea@innoenergy.com for information on special price and admission.
As an impact company, Schneider Electric is committed to address one of the biggest challenges of our time: Climate Change. With Intencity, we put all our expertise to build an environmental-friendly building, which makes the most of data, A.I., solar panels, wind turbines, building management System…
We are very proud to share this project with the EIT InnoEnergy students. They are part of this innovative journey as they are asked to provide new ideas which will contribute to make this building even smarter.