Python and Jupyter for Science Crashcourse!

Python and Jupyter for Science Crashcourse!

We believe that Python is the best and modern way to assist you in Science and Engineering and we would love to teach it to you! :)

With this course we want to show you the full arsenal of libraries and toolboxes we like in Python! With this course we want to raise the bar and lift you up on a higher level than most basic Udemy courses do!

This course offers a really practical approach and we will build real projects. We will dive right into the practial work! But don't worry if necessary we will help with additional Information and background knowledge! Also no special Science knowledge is necessary to follow along!

This course is suitable for Students, Scientists, Engineers, Students, PhDs and everyone interested in the field scientific working with Python. It is also perfect for everyone that has to write a thesis and wants to learn how to manipulate and visualize the Data in the best and most professional way. For Beginners we offer a basic chapter with an Introduction to Python!

Python is one of the most used programming languages, easy two learn, open source and offers a massive range of libraries for all kinds of tasks. In many jobs programming is essential nowadays! We both studied Engineering and Science, tried many different tools to analyze Data and we both believe python is the best way to do it!

Enough with the nice words. What can you expect from the course:

1. Introduction and Setup Software (Anaconda| JupyterNotebooks | Jupyterlab) -> If you just want to see if Jupyter is the right tool you can start running jupyter on a server! I prepared a mybinder server for you! (No installation necessary!)

   
   

2. Jupyter and Python basics (Syntax, Data types, Operators, control structures, Modules, Import an find Libraries, use documentation)

   
   

3. Introduction to Scientific Packages + Syntax (Pandas, Matplotlib, Numpy, SciPy ...)

   
   

4. Project 1: Experimental Data analysis (Example: Resistance of Lithium Ion Batteries) - Full automatic Workflow |  Read Data and Filter Data (Pandas) | Manipulate Data (Numpy) | Fit Data (SciPy interpolate) | Symbolic Math (SymPy) |  Statistics

   
   

5. Project 2: Numerical Simulation (Example: Heat Simulation) - Manipulate Arrays (Numpy) | Nested for loops | Heat Maps (Seaborn) | Create Dashboard with Voila

We put a lot of effort in this course and we hope you like it! :) If you have any questions don't hesitate an contact us!

NEW! Modern Data visualisation | Experimental data manipulation | Python in science applications | Numeric Simulation

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What you will learn

• Analyse experimental Data in a modern way!
• Modern Visualization techniques
• quick start to the field of (especially experimental) Data analysis

Rating: 3.95

Level: Beginner Level

Duration: 5 hours

Instructor: Nick -.