
Python for Scientists & Engineers
This course targets scientists and engineers wanting to learn or improve their skills in Python to analyze, interpret and visualize scientific data. It offers a broad overview over a variety of topics.
The knowledge and experience from these projects in addition to more than 20 years of programming experience go into the Python programming courses:
This course targets scientists and engineers wanting to learn or improve their skills in Python to analyze, interpret and visualize scientific data. It offers a broad overview over a variety of topics.
The Python for Biologists course is the next evolution of the Python for Scientists course specifically for Biologists. It covers the basics of Python, scientific data analysis and includes libraries like Biopython, HTSeq and Pysam.
Here, we look at ways to make programming easier. Avoiding common mistakes and structuring code are key learning goals. Notebook extensions, GIT and keyboard shortcuts are also covered.
The advanced plotting specialization course focuses on advanced plotting options in Python. We cover interactive plots and widgets, 3D visualizations, and the integration of plots in LaTeX documents using Overleaf and GIT.
In this course, we look at ways to improve both the single core performance and the multi core performance of Python code. We also compare the performance gains from libraries like Numba and Dask to the improvements by using faster hardware.
Dr. Maurice Maurer graduated in 2020 from the Technical University of Munich with a Ph.D. in computational physics. In his scientific work – both carried out at the University of California, Los Angeles (UCLA) and the Max Planck Institute for Plasma Physics – he developed a high performance computing (HPC) code to simulate plasma microturbulence in complex geometries. The dissertation is called GENE-3D – a global gyrokinetic turbulence code for stellarators and perturbed tokamaks.
During his masters project he already developed a parallelized code running on some of the fastest supercomputers in germany. For both the masters project and the Ph.D. project he employed Python for the postprocessing of the large data sets generated by the simulations.
Also, he is doing Python development consulting work for for various companies in regards to code review and performance optimization.
The knowledge and experience from these projects in addition to more than 20 years of programming experience go into the Python programming courses.
Reach out for bookings and questions about the Python for Scientists courses!
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