Python is the #1 programming language for Data Scientists and Machine Learning(DSML) professionals.
Learning and investing your time in Python is necessary if you want to become a DSML professional. The ecosystem around Python is very extensive and the community is very passionate and helpful to new users.
The video below walks through the a report released by Jet Brains where they surveyed the Big Data industry. As you can see, Python continues to be the #1 choice across the industry.
Now that you have decided to learn Python, you will need to learn how to;
- Run and test your Python code quickly
- Visualize data
- Run models and see results
- Develop Python scripts
- Develop Python web applications
- Develop software with Python
- and many more..
To be able to do a variety of tasks you can learn how to use Jupyter for quick prototyping and research. And you will need to learn how to use an Integrated Development Environment (IDE) for more of the Software Development aspects.
PyCharm
Jet Brains makes a very cool Python IDE called PyCharm.
Check it out. The Community edition is free.
VS Code
Another popular IDE is VS Code.
VS Code has certainly captured the imagination of DSML professionals. VS Code is free and is developed by Microsoft.
VS Code isn't specifically used for Python programming. You code code in many programming languages with VS Code. With a very large marketplace of plugins and extensions using VS Code will give you massive abilities as a DSML professional.
Python is a versatile language and is used for a variety of Software Engineering tasks in addition to being the #1 choice in DSML.
Style Guide
As you start writing code you will deal with basic challenges such as naming of variables and functions. How to create comments. You will wonder how to write clean and readable code. Styles guides provide just that. Guidance on how to write clean and readable code. They also create a form of standardization that improves knowledge sharing amongst peers and across the industry.
The Python foundation has published a style guide called PEP 8. You should read PEP 8 after you have read the Google Python style guide.
The one from Google is an easier read.
Remember these style guides are not a one-time read. You have to keep coming back to it and read it.
If you read it only when you are trying to solve the problem of naming variables you will not find an immediate answer. These style guides need to be read at leisure and with a certain regularity. Only during such readings will you "absorb" the suggestions and conventions so that they become part of your natural coding style.
Only then will the style guides work for you.