- Scope: 2h interactive session on programming functions for an efficient code design
- Level: All
- Format: Online
This training is available on demand. Please contact Rosina Preis via rosina.preis@eitmanufacturing.eu for further information.
€ 150,00
In stock
excl. 20% VAT
This training is available on demand. Please contact Rosina Preis via rosina.preis@eitmanufacturing.eu for further information.
In stock
Embark on a journey into the heart of programming with our interactive online training “Mastering Programming Functions: A Guided Exploration into Efficient Code Design”. Join us for an enlightening session where we demystify the intricacies of programming functions, empowering you to create code that is not just functional but also optimized for maximum efficiency. Through real-world examples, hands-on exercises, and expert insights, this online training is meticulously designed to enhance your coding skills, ensuring you leave with a profound understanding of how to implement and leverage functions effectively in your programming endeavours. Immerse yourself in an interactive experience that will revolutionize your programming approach.
This training is part of the learning path “Industrial Data Science” and may be combined with other sessions.
Main learning outcomes:
Who is this training for:
“Mastering Programming Functions: A Guided Exploration into Efficient Code Design” is a 2h online training which will include the following topics:
After the training, the course materials and training will be available on demand. For on-demand training and further information, please contact Rosina Preis via rosina.preis@eitmanufacturing.eu.
Traner 1: Dipl.-Ing. Linus Kohl
Linus Kohl works as a research associate at TU Wien and Project Manager at Fraunhofer Austria. He has experience in leading and managing research projects involving topics related to predictive and prescriptive maintenance, data analytics and developing novel machine learning solutions.
Trainer 2: Dipl.-Ing. Theresa Madreiter
Theresa Madreiter works as a research associate at TU Wien and Fraunhofer Austria. She has experience in leading and managing research projects. Her focus is on utilizing data for improved maintenance solutions, with a specialty in predictive maintenance and the analysis of unstructured data.