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SAS Energy Data Analytics and Forecasting Using algorithms for the energy turnaround

Over the course of a week, you will learn to apply algorithms in use cases related to photovoltaics, e-mobility, storage or optimization of self-consumption with a view to facilitating load and production forecasting.

Overview

In this course we consider how machine learning can be used to help solve the energy forecasting problem. You will apply those algorithms to specific use cases regarding photovoltaics, e-mobility, storage or self-consumption optimization in order to predict load and/or production. Real-world data will be used and practical experience will be provided by the experienced lecturers, that facilitate the course. Through your individual project you will have practical examples that can be taken forward in your professional life.

  • Load and production forecasting
  • Use cases regarding photovoltaics / wind, e-mobility, storage or self-consumption optimization
  • Individual coaching
  • Project thesis

Facts

Start

February 15, 2027

End

End of February 2027

Application deadline

two weeks before the course starts

Duration

5 days

Course costs

CHF 2'200.-

Head
Information events
Degree

Certification Short Advanced Studies Hochschule Luzern/FHZ in Energy Data Analytics and Forecasting 

Type

SAS

ECTS

2

Language of instruction
  • English
Venue

Horw

Target group
  • Distribution system operators
  • Self-consumption communities
  • Energy optimization companies
  • Energy specialists
  • Consulting companies
Requirements

Standard: A tertiary degree (ETH/University, college, or higher vocational education) and at least two years of professional experience.

Sur-Dossier: Individuals without a tertiary degree but with an equivalent qualification and several years of professional experience may be admitted in exceptional cases and in limited numbers via a standardised admission procedure (sur-dossier). This includes the requirement to attend the fee-based course " Academic Research and Writing" should you later decide to apply for a Certificate of Advanced Studies (CAS). Details can be found here.

If you are unsure about the classification of your degree, our Continuing Education ABC will help you.
You can find comprehensive explanations of the admission requirements inthe final provisions. 

If you are attending this program as a continuing education course without proof of performance or ECTS credits, there are no formal admission requirements.
Provider(s)

Engineering and Architecture
Continuing Education
Institute of Electrical Engineering IET
CC Digital Energy and Electric Power

Methodology

Lectures, training and coaching, project report

Remarks

This course is developed in collaboration with the Bachelor’s degree programme in Electrical Engineering and Information Technology. In addition, you will benefit from two individual coaching sessions.

This SAS can also be completed as a continuing education course. In this case, no proof of performance is required and no ECTS credits are awarded.