June 1, 2022
link will follow
Europe/Berlin timezone
++++ If the workshop is fully booked, please register for the waiting list +++++++++

A tilted view on a black screen with python code.This is a second course which is organized by PIER due to high demand for the first course (https://indico.desy.de/event/32340/).

In the five-day course “Advanced Python - Analysis and Visualization of Scientific Data” the
participants learn the most fundamental skills for analyzing (large) scientific data sets using
Python and Jupyter Notebooks.

The course will take place in five sessions on

Wed, June 1, 9am - 12.30pm

Wed, June 8, 9am - 12.30pm

Wed, June 15, 9am - 12.30pm

Wed, June 22, 9am - 12.30pm

Wed, June 29, 9am - 12.30pm

Each of the five course days consists of lectures and exercises. In the exercises, the participants are encouraged to work on their own data sets, if

The specific content of the course is:

Day 1: Brief revision of Python Syntax and Jupyter notebooks, first data analysis and visualization with Numpy and Matplotlib. Discussion of participants’ projects.

Day 2: Treating larger data sets with Numpy and Pandas.

Day 3: Visualization of data with Matplotlib, version control with git.

Day 4: Fitting and filtering of data, virtual environments.

Day 5: Brief introduction to parallelization, symbolic calculations.

About the Trainer:
Dr. Alexander Britz is a trainer, coach and facilitator specialized on working with young scientist. Next to science and academia, he is passionate about innovation, sustainability, diversity, and community. As part of his mission, he is continuously working on developing novel teaching and learning formats and finding new ways to elevate science. To learn more about him, visit www.alexbritz.de.

By education Alexander is an interdisciplinary scientist between chemistry, physics, and materials science. In his scientific career he used X-rays, lasers, and electron beams to investigate ultrafast dynamics of novel materials and chemical systems. When teaching this Python course, he draws on his experience as a scientist analyzing and interpreting experimental data from large scale facilities such as XFELs and synchrotrons.






link will follow


There is an open survey.