Python for Scientists and Engineers course

     Python for Scientists & Engineers

Summary

Scientists need programming skills in Python to analyze their data but have rarely had any programming education during their Bachelor’s and Master’s degrees. Therefore, the Python for Scientists & Engineers course has two distinct goals and teaches

  • to analyze, interpret and visualize scientific data to create publication ready plots
  • good programming practice, version control with GIT and virtual environments
News: As of 2023, the former specialisation courses “Good Programming Practice in Python” and “Advanced Plotting in Python” are now integrated into the Python for Scientists and Engineers course and the usage of AI tools is covered as well.
 

Target groups

The course is suited for people with previous experience in other programming languages and for people who already have experience with Python looking to improve their skills. A lot of previous participants have been self-taught and appreciated the structured introduction to Python and the variety of topics covered in this course.

The course is also suitable for absolute beginners in programming, however, beginners should plan to invest additional time between tutorials to learn fundamentals from the additional resources.

Course structure

The course is held in English. It can be taken on-demand or as a blended learning course. The on-demand modules each contain

  • a 60-90 minute video lecture that participants can watch when it suits them
  • exercises for the participants to apply what they have learned
The blended learning modules each additionally contain a live Zoom tutorial to answer questions (90-120min).
Participants should plan to invest 6 hours per module or  42 hours in total.
 

Content

Installation

  1. Introduction, Jupyter, Virtual Environments, Notebook extensions, Python fundamentals

Basics

  1. Syntax, PEP8, Keyboard shortcuts, Introduction to Numpy and Matplotlib
  2. Advanced Numpy, Pandas, File Input & Output, ChatGPT
  3. Advanced Matplotlib, Inset Plots, Contour Plots, Interactive Plots

Advanced topics

  1. GIT, String Formatting, Video Creation, Notebook Structure
  2. Interpolation, Fitting, Complex Fitting, Filtering, Data analysis example
  3. Creating Files, Generators, Parallelization, Sympy, Integration of Plots to Overleaf

FAQ (Frequently Asked Questions

While it is not necessary to have prior experience, it definitely helps. For example, people with a MATLAB background have historically had an easier time taking the course than absolute beginners. However, as long as you plan in extra time this course will get you from 0 to a level where you feel confident to handle your scientific data.

The lecture videos are roughly 1 hour per module, but people usually watch them twice. You should plan an extra 2 to 4 hours for the exercises and if you booked the blended learning option which is another 2 hours per module.

In total that equates to 5 to 8 hours per module

Yes. During the tutorials we will first discuss the lecture and the solution to the exercises. After that there is almost always time to discuss topics that go beyond the content of the module. Here, we often talk about the participants own programming projects.

If you actively participate in the tutorials and present solutions to the exercises you will receive a certificate at the end of the course.

If you opt for self-study using the on-demand course and still want a certificate, you can schedule a one-on-one Zoom call to assess your understanding of the concepts. Passing the test earns you the certificate. Reach out to us if interested.

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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Course & Dates
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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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Contact

Are you interested or have any questions about the Python for Scientists & Engineers course? Reach out any time!

+49 156 78448154

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