Python for MATLAB Fans From Newbie to Superb

Learn how to start using Python as a powerful, comprehensive, and solid alternative tool to MATLAB: From A to Z.

What you'll learn
How to make a smooth transition switch from Matlab to Python
Learn the fundamentals and basics of Python as a multi-purpose computational programing language
Learn how to create lists, arrays, matrices, for-loops, while-loops, if statements, functions, objects in Python
Lear how to build practical real life applications and prototypes with Python
Lear the main and key differences between Python and Matlab and why the industry prefers Python over Matlab
Learn how do regression, curve fitting, optimization, testing, machine learning using Python
Learn all what you need in order to replicate the experience of MATLAB but with Python
Learn all the key core differences between MATLAB and Python and how to consider this while using Python
Learn all the Important similarities between MATLAB and Python and how to make use of this while using python
Learn Strategies and Techniques for converting your MATLAB codes into Python Codes
Learn how to use NumPy arrays as alternatives to MATLAB matrices
Learn How indexing and slicing actually work in python and how it is different from MALTAB

Requirements
Having a Desire to learn how to use Python as an alternative tool to Matlab
Having Basic Knowledge in programing languages or coding
Having the will to dedicate 7 hours of your time to learn and master the topic
Description
Python for MATLAB Fans and long-standing Users: From Newbie to Superb

In this course, you will learn how to start using Python as a powerful, comprehensive, Machine Learning oriented, and solid alternative tool to MATLAB: From simulation to prototype to real life production applications, all in the same language.

If you are not yet a user of Python, and its move to become the most common programming language has piqued your interest, then you are in the right place.

This course is designed and targeted for MATLAB fans and long-standing users, who are considering moving to Python, either partially or totally.

Python has become one of top used languages in the world in many fields including science, engineering, machine learning, and data science with a lot of momentum. Many top high profile projects and applications use it and more are transitioning to it all the time. The reason behind this is that Python is completely free, but more importantly, it is because Python has a thriving ecosystem of packages that allow developers to work faster and more efficiently. They can go from simulation to prototyping to production to scale on hardware ranging from a Raspberry Pi (or maybe micro controller) to a cluster, all using the same language. A large part of Python’s growth is driven by its excellent support for work in the fields of science, engineering, machine learning, and data science.

You might be thinking about switching from MATLAB to Python to get access to the ecosystem and increase your productivity, but you might also have some outstanding questions and concerns, such as: How do I get started? Will any of my knowledge transfer? How different are Python and MATLAB? How long will it take me to become proficient? Is it too big a of a shift? Can I transition gradually or do I have to do it all at once? .

We know people put a lot of thought into the tools they select and that changing platforms is a big deal. So, we created this course to help you make the right choice.

In this course, we give you the key information and insight you need to quickly evaluate whether Python is the right choice for you and your team, including: How to get started, What you need in order to replicate the MATLAB experience, Important conceptual differences between MATLAB and Python, Important similarities between MATLAB and Python: What MATLAB knowledge will transfer, Strategies for converting existing MATLAB code to Python, How to accelerate your transition.

So, in a nutshell, you will learn the followings from this course:

How to make a smooth transition switch from MATLAB to Python

The fundamentals and basics of Python as a multi-purpose computational programing language

How to create lists, arrays, matrices, for-loops, while-loops, if statements, functions, objects in Python

How to build practical real life applications and prototypes with Python

The main and key differences between Python and MATLAB and why the industry prefers Python over MATLAB

How do regression, curve fitting, optimization, testing, machine learning using Python

All what you need in order to replicate the experience of MATLAB but with Python

All the key core differences between MATLAB and Python and how to consider this while using Python

All the Important similarities between MATLAB and Python and how to make use of this while using python

Strategies and Techniques for converting your MATLAB codes into Python Codes

How to use NumPy arrays as alternatives to MATLAB matrices

How indexing and slicing actually work in python and how it is different from MALTAB

=============

In addition, the course explores common tasks when doing data analysis or running simulations, with a focus on the most common packages used for each task, such as loading data, cleaning and reformatting data, performing analysis or simulation, plotting, and saving data.

=========

Why transition from MATLAB to Python?

If you’re unsure of whether you’d like to transition to Python, we’ve collected some of the most commonly cited reasons for the change. Cost is often the first reason given, as licensing fees add up quickly and may account for a significant part of a small organization’s budget. Python has the appeal of being free, because you do not have to pay a license fee and you have access to many free open source packages.

Choosing Python – or any other open source language – lets you run your code without being locked-in with a given provider. There is no need to pay a license fee in order to keep your software running. More importantly, it means that colleagues, and others, can run Python code without requiring a license. This can greatly improve the chances of survival for your project.

Finally, Python has the benefit of being a general purpose programming language. Though it is an excellent language for scientific computing, it is not solely a scientific computing language. It can be used to do everything from building a file synchronization system, a photo-sharing service, a 3D modeling and video-editing application, and a video hosting platform, to discovering gravitational waves.

The consequence of such varied uses is that you can find tools to do almost all common tasks. This allows you to use Python for your entire application, from hardware control and number crunching, to web API and desktop application. And for cases when a feature or a library exists only in another language, Python can easily interface with C/C++ and Fortran libraries. There are also Python implementations for some of the major other languages, such as IronPython for C, and Jython for Java.

==========

Build your Python skills: Researcherstore offers a number of Python training courses for those looking to improve their skills. If you are currently a MATLAB user, we recommend Researcherstore Python for Scientists and Engineers as the perfect entry point into the scientific Python world.

Who this course is for:
Students, who are considering to start using Python
Developers, who are considering switching to Python
Researchers, who are considering moving to Python
Scientists, who are considering migrating to Python
Academics, who are considering to start using Python
Engineers, who are considering moving to Python
MATLAB users, who are considering transitioning to Python, partially or totally.