Python is a programming language that has relatively simple syntax. This makes it an ideal choice for beginners who are just starting out in the field of programming.

Although Python 2 has its merits, learning Python 3 is more advantageous, especially for beginning developers. The following are the top reasons why you should learn Python 3. Python 3 improves AI, machine learning, and data science support.

It is advisable for beginners to start coding with python because it’s known to have relatively easy syntax structure for reading purposes. Here's a step-by-step guide on how to begin coding with Python:  

Install Python: To begin with, one has to have python installed in their own personal computers. They should visit the python site to download the current version, then install it as appropriate for their OS.

Choose a Text Editor or IDE: In order to write and run python code, one needs either a code editor or an integrated development environment (IDE). These include Visual Studio Code, PyCharm, Jupyter Notebook, and IDLE (which comes with Python).

Write Your First Python Program: Fire up your preferred code editor or IDE and generate a fresh Python file with a .py file extension. Begin with a basic “hello, world” program.

Run Your Code: Next, you can have your Python code executed. Most of the code editors and IDEs contain a “run” or “execute” key. As an alternative, you may also run your code from the command line whereby you navigate to the Python file’s location and use the python command.

Learn the Basics: Commence with the fundamentals of Python such as variables, datatypes (integers, strings, arrays, etc) and simple maths expressions. You might also want to refer to python’s official documentation, or simply look over the web for some python based tutorials and courses.

Control Structures: Understand how to utilize control structures such as if statements, loops in for and while and functions, respectively.3 These are basics on which more complicated programs are built.

Use Libraries and Modules: If your focus is scientific computing, you may look into NumPy; for data analysis, into pandas or maybe at web development with Flask or Django library or something else. Online Resources and Communities:  

• There is a variety of online learning centres and communities for Python. Useful sites include Codecademy, Coursera, edX, and StackOverflow.