How should I start learning Python?

Data Science, AI and ML
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How should I start learning Python?

Python is a sophisticated, open-source, high-level, and widely used programming language. It is a basic, object-oriented, interpreted, and high-level programming language. It is mostly utilized in web development, mathematical and scientific application development, data science, machine learning, and a variety of other applications.

Python has the following applications:

Data Analysis

Artificial Intelligence

Machine Learning

Automation

Build Web Apps

Software testing

If you are a beginner programmer, Python might be a good place to start because it is at the top of the list of best programming languages but is also the most profitable to learn.

Learn Syntax and Fundamentals:

  • Basic arithmetic in the Python shell.

  • Structures of control.

  • Accepting user input, Strings, and Typecasting

  • Python looping: For and While loops

  • Exceptions handling

  • Imports, Modules, and Functions

  • Functions

The OOPS idea, as well as built-in data structures:

This part will be challenging, especially if you are unfamiliar with object-oriented programming ideas.

  • Python’s OOPS
  • Dictionary, List, and Tuples
  • String formatting
  • Lamdas
  • Regular expressions

It’s time to develop something once you’ve learned the preceding topics and practiced them sufficiently. Python has a large library of modules, packages, libraries, and frameworks that you can use for a wide range of applications. Rather than starting from scratch, use the frameworks and libraries provided in this language. Using these frameworks and libraries will make it a lot easier for you to create anything. Choose the framework or libraries based on your final aim (Web development, desktop-based applications, etc.)

Frameworks for Web Development: Python has a plethora of frameworks for developing web applications.

Django is a high-level web framework that is commonly used for web development in startups and organizations. It adheres to the MVC design pattern and supports a variety of databases including PostgreSQL, MySQL, SQLite, and Oracle.

Flask: Flask is one of the simplest Python microframeworks to learn. Flask is a good choice if you want to create a basic A web application. Although it is not as sophisticated and extensive as Django, it does provide capabilities like unit testing and the ability to develop REST APIs.

To Create Desktop Applications:

Tkinter, PyQT, Kivy, WxPython, and PyGUI are excellent libraries for creating desktop-based applications.

Tkinter: Tkinter is an open-source package that allows you to create desktop graphical user interface (GUI) programs in Python. Tkinter is easy to learn and has a graphical interface.

PyQT: PyQt is one of Nokia’s most powerful cross-platform GUI libraries. Python programming is combined with the Qt library. It is useful for creating graphical user interfaces for desktop applications.

Kivy: It can be used to construct desktop programs and is compatible with platforms such as Android, iOS, Linux, and Raspberry Pi.

Data analysis:

Numpy, Pandas, Seaborn, Bokeh, SciPy, and Matplotlib are useful libraries for data analysis. These libraries are beneficial to people aspiring to be data analysts or data scientists.

In terms of Machine Learning:

TensorFlow: Google’s most popular deep learning library. It is a computational framework for expressing algorithms that employ a large number of Tensor operations.

Scikit-Learn is a Python machine learning framework that works with numerical libraries such as SciPy and NumPy.

Resources for Learning:

Board Infinity: https://www.boardinfinity.com/learner/dashboard

It has the following features:

Mentor Assistance: Mentors will assist you in the form of an explanation of doubts as well as the resolution of other issues. Live chat and video sessions are channels via which students may ask questions/and clarify their worries.

Placement Assistance: Using a network of global organizations, they may link your interview call with companies and so position you. These interviews are scheduled based on the student’s merit and the job profile.