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Plan du cours
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
Pré requis
- Experience with Matlab programming.
Audience
- Data scientists
- Developers
14 heures
Nos Clients témoignent (5)
Exemples/exercices parfaitement adaptés à notre domaine
Luc - CS Group
Formation - Scaling Data Analysis with Python and Dask
Traduction automatique
Le formateur était très disponible pour répondre à toutes les questions que je me posais.
Caterina - Stamtech
Formation - Developing APIs with Python and FastAPI
Traduction automatique
Transfert des connaissances pratiques et de l'expérience du formateur.
Rumel Mateusz - Pojazdy Szynowe PESA Bydgoszcz SA
Traduction automatique
It was a though course as we had to cover a lot in a short time frame. Our trainer knew a lot about the subject and delivered the content to address our requirements. It was lots of content to learn but our trainer was helpful and encouraging. He answered all our questions with good detail and we feel that we learned a lot. Exercises were well prepared and tasks were tailored accordingly to our needs. I enjoyed this course
Bozena Stansfield - New College Durham
Formation - Build REST APIs with Python and Flask
As I was the only participant the training could be adapted to my needs.
