Course Outline
Introduction
- Open-Source General-Purpose vs. Proprietary or Specialized Tools
Establishing a Python Environment for Data Science
Leveraging Matlab's Strengths in Numerical Problem Solving
Exploring Python Libraries and Packages for Numerical Analysis and Data Science
Practical Application of Python Syntax
Data Ingestion into Python
Handling Matrix Operations
Performing Mathematical Calculations
Data Visualization Techniques
Migrating Existing Matlab Applications to Python
Identifying and Avoiding Common Pitfalls During the Transition
Interoperability: Calling Matlab from Python and Vice Versa
Using Python Wrappers to Mimic a Matlab-like Interface
Wrap-Up and Final Thoughts
Requirements
- Prior experience with Matlab programming.
Target Audience
- Data Scientists
- Developers
Testimonials (2)
everything was perfect
Florin Vrincianu
Course - Python Programming Fundamentals
Hands-on exercises related to content really helps to understand more about each topic. Also, style of start class with lecture and continue with hands-on exercise is good and helpful to relate with the lecture that presented earlier.
