Course Outline
Introduction
- Free and General-Purpose Tools vs. Proprietary or Specialized Tools
Establishing a Python Development Environment for Data Science
Leveraging Matlab’s Strengths in Numerical Problem Solving
Utilizing Python Libraries and Packages for Numerical Analysis and Data Science
Practical Application of Python Syntax
Data Ingestion into Python
Matrix Operations and Manipulation
Performing Mathematical Calculations
Data Visualization Techniques
Porting Existing Matlab Applications to Python
Navigating Common Challenges During the Transition to Python
Interoperability: Calling Matlab from Python and Vice Versa
Creating Python Wrappers for a Matlab-Style Interface
Summary and Conclusions
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.
