Python and Jupyter for Science Crashcourse!

Python and Jupyter for Science Crashcourse!, available at $34.99, has an average rating of 4.1, with 33 lectures, based on 25 reviews, and has 172 subscribers.

You will learn about Analyse experimental Data in a modern way! Modern Visualization techniques quick start to the field of (especially experimental) Data analysis Understand how to use the the Internet/ Documentation to find soultions for your own Problems This course is ideal for individuals who are Students, Scientists, Engineers, Physics, Chemistry, Data science, Data visualization! It is particularly useful for Students, Scientists, Engineers, Physics, Chemistry, Data science, Data visualization!.

Enroll now: Python and Jupyter for Science Crashcourse!

Summary

Title: Python and Jupyter for Science Crashcourse!

Price: $34.99

Average Rating: 4.1

Number of Lectures: 33

Number of Published Lectures: 33

Number of Curriculum Items: 33

Number of Published Curriculum Objects: 33

Original Price: €149.99

Quality Status: approved

Status: Live

What You Will Learn

Analyse experimental Data in a modern way!
Modern Visualization techniques
quick start to the field of (especially experimental) Data analysis
Understand how to use the the Internet/ Documentation to find soultions for your own Problems

Who Should Attend

Students, Scientists, Engineers, Physics, Chemistry, Data science, Data visualization!

Target Audiences

Students, Scientists, Engineers, Physics, Chemistry, Data science, Data visualization!

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 likein 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 wantsto learn how to manipulate and visualize the Data in the best and most professional way.For Beginnerswe 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:

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!)
Jupyter and Python basics (Syntax, Data types, Operators, control structures, Modules, Import an find Libraries, use documentation)
Introduction to Scientific Packages + Syntax (Pandas, Matplotlib, Numpy, SciPy …)
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
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!

Course Curriculum

Chapter 1: Introduction

Lecture 1: What to expect from this course?

Lecture 2: How to use the course material

Chapter 2: Tools

Lecture 1: Anaconda

Lecture 2: Jupyter Notebooks

Lecture 3: Jupyter notebook Text Cells/Markdown

Chapter 3: Python Basics

Lecture 1: Python general remarks

Lecture 2: Variables and operators

Lecture 3: Data types

Lecture 4: Exercise 2: write a function!

Lecture 5: Control structures

Lecture 6: Style guide

Lecture 7: Modules

Lecture 8: Packages

Lecture 9: Classes and Objects

Chapter 4: Important scientific packages

Lecture 1: Handle Tabular Data: Pandas

Lecture 2: Numpy – Arrays

Lecture 3: Sympy – Symbolic Math

Lecture 4: Visualization 1: Matplotlib

Lecture 5: Visualization 2: Seaborn, Bokeh, Plotly, Voila

Chapter 5: Project 1: experimental Data analysis (Example: Lithium Ion Battery)

Lecture 1: Introduction to the project

Lecture 2: Reading txt files with Numpy (loadtxt)

Lecture 3: Reading files with pandas (read_)

Lecture 4: Exploring the data, Filter data, Errorbars, Mean Values

Lecture 5: Plotting the data

Lecture 6: Fit data

Chapter 6: Project 2: numerical Simulation (Heat Exchange)

Lecture 1: Introduction

Lecture 2: Theory

Lecture 3: Digression 1: Manipulation Numpy-Arrays

Lecture 4: Assign boundary conditions

Lecture 5: Digression 2: Heat Maps

Lecture 6: Heat map and preparation for the calculation

Lecture 7: Digression 3: for loops

Lecture 8: Calculation

Instructors

Nick -.
Engineer and web instructor

Rating Distribution

1 stars: 0 votes
2 stars: 1 votes
3 stars: 2 votes
4 stars: 10 votes
5 stars: 12 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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