Python for Scientists and Engineers course


Example lecture

To give you an idea what the courses look like, here it is an example lecture video about interpolation.

Example tutorial

The optional tutorials are there to fix issues, answer questions and to go beyond the lecture materials. The tutorials are highly dependent on the participants and no two tutorials are ever going the same way. So take this video only as an example of how a tutorial can go:

What participants say

"Maurice's course is a great introduction targeted towards the most important aspects of Python for scientists such as data analysis and visualization. His lectures and exercises are highly motivating and get you started writing relevant programs straight away. His classes are fun and informative, you can ask any question and always get a useful answer. I highly recommend it!."
"Maurice showed us a lot of powerful tools in Python that can be applied in scientific research. Actually, I already started to use what I learned from this course to deal with my experimental data. Thank you Maurice!"
"As an absolute beginner in Python I was brought to a level where I feel confident to analyze my data using Python."
Stree Vithya Arumugam
"I liked the broad overview of different topics related to scientific working with Python"
Ph.D Student
"I took my first steps into coding with python. The examples and especially the readdressing of common used code to load data, plot it and analyze it made it a hands on course. The course is nicely structured and the live tutorials help a lot. I can only recommend it."

Course overview

Module / Course​ Python for Scientists​ Python for Biologists Python Basics
Introduction, Virtual Environments, Jupyter, Notebook extensions, Python Fundamentals + + +
Syntax, PEP8, Keyboard Shortcuts, First examples in Numpy and Matplotlib + + +
Advanced Numpy, File IO, Pandas, ChatGPT + + +
Advanced Matplotlib, Plotting options, Inset Plots, Contour Plots, Interactive Plots + + +
GIT, String Formatting, Video Creation, Notebook structure + +
Interpolation, Fitting, Complex Fitting, Filtering, Data analysis example + *
Creating Files, Generators, Parallelization, Sympy, Integration of Plots to Overleaf + *
Biopython, DNA sequencing, BLAST, Visualization of DNA *
Image analysis and processing, Scikit Image *
+ meaning the topics are both covered in the lecture and the tutorials
* meaning participants have access to the lecture materials but we will pick 1 or 2 topics to discuss in the tutorials

On-demand courses

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Upcoming Live Courses

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Python for Biologists course
Dates: | 17.10. | 24.10. | 31.10. | 21.11. | 28.11. | 5.12. |
Time: 9:00-11:00am German time
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Are you interested or have any questions about the Python for Scientists & Engineers course? Reach out any time!

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