Course Outline
Introduction
- Comparing Free and General-Purpose vs. Non-Free or Specialized Tools
Configuring a Python Development Environment for Data Science
Leveraging Matlab for Numerical Problem Solving
Utilizing Python Libraries and Packages for Numerical Analysis and Data Science
Practical Application of Python Syntax
Data Import Procedures in Python
Matrix Operations
Mathematical Operations
Data Visualization Techniques
Porting an Existing Matlab Application to Python
Addressing Common Challenges During the Transition to Python
Interoperability: Calling Matlab from Python and Python from Matlab
Employing Python Wrappers for Matlab-Compatible Interfaces
Summary and Key Takeaways
Requirements
- Prior experience in Matlab programming.
Target Audience
- Data scientists
- Software 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.
