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 (5)
Examples/exercices perfectly adapted to our domain
Luc - CS Group
Course - Scaling Data Analysis with Python and Dask
Very interactive with various examples, with a good progression in complexity between the start and the end of the training.
Jenny - Andheo
Course - GPU Programming with CUDA and Python
Very good preparation and expertise of a trainer, perfect communication in English. The course was practical (exercises + sharing examples of use cases)
Monika - Procter & Gamble Polska Sp. z o.o.
Course - Developing APIs with Python and FastAPI
Helpful and good listener .. interactive
Ahmed El Kholy - FAB banak Egypt
Course - Introduction to Data Science and AI (using Python)
Trainer develops training based on participant's pace