This training introduces High-Performance Data Analytics (HPDA) through interactive Jupyter notebook exercises. You will learn how to use Python with libraries such as Pandas and Dask for efficient large-scale data analysis. The course explains the fundamentals of High-Performance Computing (HPC) and High-Throughput Computing (HTC), showing how both support scalable data processing and performance optimisation. It is intended for researchers, engineers, and data scientists aiming to accelerate their analytics workflows.
Technical prerequisites:
* Working knowledge of Python and basic experience Jupyter notebooks
Duration
4 hours
Trainers
Leszek Grzanka (ACC Cyfronet AGH / AGH University of Krakow / IFJ PAN):
Data analysis and HPC expert specializing in Monte Carlo simulations and large-scale scientific computing for particle and nuclear physics applications at CERN and IFJ PAN.
Klemens Noga (ACC Cyfronet AGH): HPC Software Specialist with significant experience in supporting PLGrid infrastructure users.
Training language
Polish or English, depending on the registered participants.
