Master Python programming by solving scientific projects
What you'll learn
- Python
- Scientific programming
- Data visualization
- Time series analysis
- Modeling
- Regular expressions
- Spectral analysis
- Filtering
- Data clustering
- Gradient descent
- Text processing
- Data projects
- Data animation
Requirements
- Know how to use a computer!
- Motivation to learn Python coding
Description
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
Featured review
![Ihshan Gumilar](data:image/svg+xml,%3Csvg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 64 64"%3E%3C/svg%3E){kind=avatar}
Instructor
- 4.7 Instructor Rating
- 39,021 Reviews
- 206,382 Students
- 23 Courses
I am a neuroscientist (brain scientist) and associate professor at the Radboud University in the Netherlands. I have an active research lab that has been funded by the US, German, and Dutch governments, European Union, hospitals, and private organizations.
But you're here because of my teaching, so let me tell you about that:
I have 20 years of experience teaching programming, data analysis, signal processing, statistics, linear algebra, and experiment design. I've taught undergraduate students, PhD candidates, postdoctoral researchers, and full professors. I teach in "traditional" university courses, special week-long intensive courses, and Nobel prize-winning research labs. I have >80 hours of online lectures on neuroscience data analysis that you can find on my website and youtube channel. And I've written several technical books about these topics with a few more on the way.
I'm not trying to show off -- I'm trying to convince you that you've come to the right place to maximize your learning from an instructor who has spent two decades refining and perfecting his teaching style.
Over 120,000 students have watched over 7,500,000 minutes of my courses. Come find out why!
I have several free courses that you can enroll in. Try them out! You got nothing to lose ;)
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By popular request, here are suggested course progressions for various educational goals:
MATLAB programming: MATLAB onramp; Master MATLAB; Image Processing
Python programming: Master Python programming by solving scientific projects; Master Math by Coding in Python
Applied linear algebra: Complete Linear Algebra; Dimension Reduction
Signal processing: Understand the Fourier Transform; Generate and visualize data; Signal Processing; Neural signal processing