Course Outline
Introduction
- Free and General Purpose vs Not Free or General Purpose
Setting up a Python Development Environment for Data Science
The Power of Matlab for Numerical Problem Solving
Python Libraries and Packages for Numerical Problem Solving and Data Analysis
Hands-on Practice with Python Syntax
Importing Data into Python
Matrix Manipulation
Math Operations
Visualizing Data
Converting an Existing Matlab Application to Python
Common Pitfalls when Transitioning to Python
Calling Matlab from within Python and Vice Versa
Python Wrappers for Providing a Matlab-like Interface
Summary and Conclusion
Requirements
- Experience with Matlab programming.
Audience
- Data scientists
- Developers
Testimonials (1)
Concrete, hands-on exercises that were relevant to our core business. Having a trainer with a scientific background was a real asset because we could delve into deeper discussions, not just about programming but also about science and how to combine the two. The practical sessions in Jupyter Notebook format were interesting.
Victor - Vermon
Course - Python for Matlab Users
Machine Translated
