Learn Python via Cool Projects

 

Python_for_Scientists small

 

The Python for Scientists and Engineers course,  based on my highly successful Kickstarter, seeks to teach you advanced Python by building awesome projects.

Practice, not theory

The course will be heavily practical, with little or no theory. The goal is to get you using Python for real world engineering applications. For each topic, we will choose a real case scenario and build a quick solution in Python to solve our problem.

These are the topics we will cover:

Introduction to Python

I will cover the basics of the Python, specifically for the programmers wanting to use Python for engineering.This will be a quick introduction to Python for people who know at least one other programming language.

Image and Video processing

  • Detect faces in images and video

abba_face_detected

  • Count objects in an image
  • Detect color of a shirt
  • Detect Motion

motion2

 

Audio

Create a sine wave, find its frequency, simple filtering

noisy4

Analysis and plotting with Numpy, Scipy and Matplotlib

Learn how to work with and graph scientific data

 

audacity3

 

Machine Learning

Build an Amazon like recommendation engine in Python.

Marvin_(HHGG)

 

Statistics and data manipulation

The Python pandas library is Python’s answer to R, and used extensively in financial analysis.

 

Turn your Raspberry Pi into a web server

300px-RaspberryPi

Learn how to control your Pi via a web browser, using your laptop or even iPad:

rpi

 

Buy now:

These options are for individuals. Teams, please contact me.

Option 1. Get the book, all the code, plus a Virtual Machine to run the examples.

Price: $39

I want this

Option 2: Get the above, plus videos of all the courses.

Price: $99
I want this

 

Also available on LeanPub.

Want to pay by Paypal? Contact me.

FAQ

1. What’s this Virtual Machine I will get?

The biggest hassle with projects like these is installing libraries, struggling with version differences, 32/64 bit versions of libraries, etc. You can spend more time installing libraries than running the code. For this reason, I will create a Virtual Machine and do most of the testing there. You can have this VM too. It means you can start coding immediately, without wasting any time installing libraries.