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 (4)
Examples/exercices perfectly adapted to our domain
Luc - CS Group
Course - Scaling Data Analysis with Python and Dask
The fact of having more practical exercises using more similar data to what we use in our projects (satellite images in raster format)
Matthieu - CS Group
Course - Scaling Data Analysis with Python and Dask
The trainer was very available to answer all te kind of question I did
Caterina - Stamtech
Course - Developing APIs with Python and FastAPI
Transfer of practical knowledge and experience of the trainer.
Rumel Mateusz - Pojazdy Szynowe PESA Bydgoszcz SA
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