Master Python programming by solving scientific projects
Learn practical coding in Python from a warm-blooded scientist. Each video includes hands-on solved practice problems!
What you’ll learn
Time series analysis
Know how to use a computer!
Motivation to learn Python coding
You’re probably thinking “There are hundreds of Python courses on Udemy; why should I enroll in this one??!?”
Let me skip all the blah blah blah you often read in these course descriptions, and get straight to what makes this course stand out:
- Strong focus on solving projects that you will encounter in your academic, work, and hobby projects.
- I use a problem-solving teaching style focused on getting results. The course is much more than just a list of Python functions.
- I’m not a member of the Python cult (you know, the people who believe Python is The Greatest Language Ever). So I’m not going to gloss over the weird or annoying parts of Python that many instructors ignore or pretend aren’t a problem.
- The course contains a wide variety of projects, from statistics to data clustering to text processing to time series filtering. You’ll also get to learn really cool things like simulating a brain circuit, plotting state-space trajectories, biomedical signal processing, and the math behind gradient descent.
- Access to the course Q&A, where I and your fellow students can discuss Python coding strategies, data types, best-practice in scientific coding, and so on.
- I encourage students to contribute their clever project solutions to the Q&A forum, so you can also learn from your colleagues. And, of course, you can post your own clever code solutions to help your fellow students!
What should you do now?
- Check out the preview videos so you can see my teaching style.
- Check out the reviews of this course.
- You can also see the reviews of my other courses to learn that I am a dedicated and passionate teacher.
Who this course is for:
- Total beginners to Python
- (optional) some experience in other languages (e.g., MATLAB or R)
- Interest in using Python for data, science, engineering, physics, biology
Created by Mike X Cohen
Last updated 3/2022
Size: 12.80 GB