Course CHARGE
Course CHARGE

Three-day course CHARGE

CHARGE is an intensive 3-day course designed for data professionals working in the energy transition. This program is organized by Alliander and Radboud University.

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General

What are you going to learn?

The CHARGE program is a 3-day intensive course, designed for data professionals working in the energy transition and jointly organized by Alliander and Radboud University. The primary objective of the CHARGE course is to deepen participants' understanding of advanced data analysis techniques, specifically on Time Series Analysis and Network Science. Furthermore, CHARGE integrates ethical and sustainable considerations of data-driven decision-making in the energy sector. Through a combination of theoretical knowledge and practical application, participants will be equipped to tackle several aspects of the complex challenges associated with the energy transition. 

By the end of the course, participants will be inspired with new concepts and know how to make the translation from theory to practical issues encountered in their work. With the long term goal of contributing to the development of innovative solutions within their organizations, driving the energy transition forward. 

After the course:

The course aims to provide participants with: 

  • Advanced Knowledge: In-depth lectures covering the latest developments and methodologies in Time Series Analysis and Network Science. 
  • Practical Skills: Hands-on experience through Alliander use case studies, enabling participants to apply theoretical concepts to real-world energy sector challenges. 
  • Ethical and sustainability awareness: A comprehensive understanding of the ethical implications of data science and AI, tailored to the energy sector, which fosters responsible and informed decision-making by reconsidering their earlier learnings through the lens of ethics and sustainability 

In addition, the course offers you the opportunity to meet and exchange experiences with professionals who face similar challenges in the energy transition. 

Logo Alliander

Collaboration

This course was developed in collaboration with Alliander.

Picture of the teachers of CHARGE

Is this course right for you?

This course is designed for data professionals working in the energy sector with a strong background in data science, AI and machine learning. It is ideal for those responsible for data-driven decision-making who are keen to deepen their technical skills while exploring the ethical dimensions of their work. 

CHARGE entry requirements

To be eligible, you must meet the following background and expertise criteria:

  • You are working as a data professional in the energy sector, with demonstrable experience in data science, artificial intelligence or machine learning.
  • You are actively involved in data-driven decision-making and problem-solving within the energy transmission, distribution or infrastructure sector.

Starting date

06 November 2024, 9 am
Location
Radboud University Campus
City
Nijmegen
Costs
€1,980
Discount
Employees and (former) students of Radboud University and Radboudumc receive a 10% discount.
VAT-free
Yes
Including lunches, coffee and tea.
Educational method
On-site
Main Language
English
Sessions
06 November 2024, 9 am - 5 pm
13 November 2024, 9 am - 5 pm
20 November 2024, 9 am - 5 pm
Number of sessions
3

Factsheet

Type of education
Course
Result
Certificate, Edubadge
Organisation
Education for Professionals

Contact information

Do you have a question about this training? Please contact us.

Programme

 

The CHARGE program is structured over three full days, each focused on a key area essential to data science in the energy sector:

  • Day 1: Time Series Analysis 

This day will focus on the principles and techniques of Time Series Analysis, a critical tool for forecasting and analyzing data trends over time. Participants will learn how to apply these techniques to energy sector challenges. 

  • Day 2: Network Science 

The second day will delve into Network Science, a powerful framework for understanding and analyzing complex networks, such as energy grids. Participants will learn how to apply these techniques to energy sector challenges. Participants will explore how to model and interpret relationships within these networks, gaining insights into system behavior, vulnerability, and optimization. 

  • Day 3: Ethics and Sustainability in Data Science 

The final day will address the ethical and sustainability considerations associated with the use of data science and AI in the energy sector. The first focus is on virtue ethics and how to conduct good science. The sustainability part will focus on the impact of AI on the energy consumption of AI solutions and ways to mitigate energy use. Participants will engage in discussions and case studies to develop a critical understanding of these issues and learn how to navigate them responsibly. 

Each day includes expert-led lectures in the morning, followed by practical case studies in the afternoon, allowing participants to apply the concepts they have learned. 

Lecturers

The CHARGE program is led by a team of distinguished lecturers from Radboud University:

• Yuliya Shapovalova is Assistant Professor of Data Science, specializing in Time Series Analysis. Yuliya has extensive experience in applying these techniques to real-world energy challenges in collaboration with industry partners, including Alliander.
• Lucia Cavallaro is Assistant Professor of Data Science, with a focus on Network Science. Her research includes the analysis of complex networks, applied to areas like energy systems and social networks.
• Luca Consoli is Associate Professor at the Institute for Science in Society. Luca’s expertise lies in the ethics of science and the societal impact of technological and scientific developments.
• Bernard van Gastel is Assistant Professor of Sustainable Digitalization, specializing in predicting the energy consumption of software and its societal impacts, including inclusion and privacy.

Additionally, professionals from Alliander and Radboud University will contribute to the program, enriching the practical sessions and ethical discussions with their real-world insights.

Costs

The cost of this course is € 1.980,00 including lunches, tea and coffee. Employees and alumni of Radboud University and Radboud university medical center receive a 10% discount. Click here to read more about discount and subsidy. 

Registration

You can register for this program by filling in the form below. Submitting the form will finalize your registration. You will receive an email confirming your registration in your inbox. If the program is full, you will be placed on a waiting list. There may be a charge if you wish to cancel. You can read more about this in our General Terms and Conditions.  

Between 7 and 14 days before the start of the program, you will receive an email containing information for the first session, and the invoice. To participate in the program, you are required to pay before the date on which it is due to commence. If you have not received anything 7 days before the start, please check your spam box and/or contact us. 

By registering, you will be sharing personal data with us. You can rest assured that we will handle your personal data with care and confidentiality. More information on this can be found in our privacy statement. 

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Admission Requirements

To be eligible for this course, you must meet the following background and expertise criteria:

  • You are a data professional in the energy sector, with demonstrable experience in data science, artificial intelligence or machine learning.
  • You are actively involved in data-driven decision-making and problem solving within the energy transmission, distribution or infrastructure sector.
I hereby declare that I meet the admission requirements.

Terms and Conditions

We would like to draw your attention to the terms and conditions of Radboud Academy. These state, among other things, that payment of the invoice must be made before the date on which the activity is due to commence, and that there may be charges if you cancel. 

Do you agree to the terms and conditions?