High-Performance Data Analytics with Python

Do you want to work faster and more efficiently with large datasets? This training will introduce you to the world of High-Performance Data Analytics (HPDA) through intensive, hands-on sessions in the Jupyter Notebook environment.

During the workshops, you will learn how to leverage the capabilities of Python and libraries such as Pandas and Dask to efficiently analyze data – from single files to datasets that exceed your computer’s memory. The training combines theory with practice, allowing you to immediately apply newly acquired skills to real-world data analysis scenarios.

What can you expect?

• Learning how to work with large datasets in Python
• A practical introduction to data analysis using Pandas
• Getting familiar with tools for scaling computations (Dask)
• Understanding how HPC (High-Performance Computing) and HTC (High-Throughput Computing) work
• Working with real datasets, including scientific data
• Hands-on exercises demonstrating the differences between local and distributed approaches
• Learning methods for optimizing performance and accelerating data processing

Who is it for? 

This training is aimed at individuals who want to develop their data analysis skills:

• researchers and academic staff
• engineers
• data scientists and analysts
• anyone working with larger datasets who wants to do it more efficiently

Requirements

To benefit fully from the training, participants should have:

• a basic understanding of Python
• familiarity with Jupyter Notebook
• willingness to work with data and learn new tools
• no prior training courses or account registration are required.