- Scope: 1,5h online training on mastering data cleaning with Python
- 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
Immerse yourself in the realm of programming with our interactive webinar “Clean Code, Clear Insights: Mastering Data Cleaning with Python”. Join us for an immersive session where we delve into the intricacies of handling and cleaning data using Python. Explore the art of transforming raw data into actionable insights through real-world examples, hands-on exercises, and expert guidance. This webinar is meticulously designed to enhance your coding skills, ensuring you leave with a comprehensive understanding of how to efficiently work with data and perform crucial data cleaning tasks. Immerse yourself in an interactive experience that will revolutionize your approach to programming for data analysis. Unleash the full potential of your datasets with precision and efficiency
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:
“Clean Code, Clear Insights: Mastering Data Cleaning with Python” is a 1,5h 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.