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Introduction to Python Programming

OVERVIEW

Python is a programming language that has gained immense popularity due to its simplicity and ease of use. It's readability and easy-to-learn syntax makes it popular with developers across multiple industries, including: Web development, data science, and machine learning.Frame 41-min.png

Introduction to Python

Python was developed by Guido van Rossum in the late 1980s and was first released on February 20, 1991. The language is named after his group Monty Python Comedy, an old BBC television sketch series ūüďļ . Many examples in the documentation and tutorials reference Monty Python sketches and movies ūüé≠.

Python has a large user community who are active ūüĎ• . This means many resources are available which can be used for learning ūüďö , and users can create their own modules for others to use. There are a lot of tutorials, books ūüďö , online courses for beginners, and many libraries and frameworks for advanced Python users, but this tutorial will help you understand Python very clearly.

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WHY USE PYTHON?

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  1. Easy to learn:ūüĎĆūüďĖ Python is meant for its simplicity and readability, making it easy for beginners who are very interested in learning Python. The language has a simple syntax similar to writing English, and its code is often referred to as "executable pseudocode," which is easy to read and understand.
  2. Versatile:ūüĒÄ Python is a programming language ūüíĽ that can be used for many applications such as web development, data science, and machine learning. A library that is standard, along with built-in functions and modules, makes it possible to write complex programs with minimal code. Also, programmers can publish their own modules.
  3. Large community: ūüĆź Python has a large and active developer community, with many resources available for learning and using the language. There are many libraries and frameworks for understanding advanced concepts.
  4. High-Level Language:ūüĒĚ Python is considered a high-level language, which simplifies many low-level details of computer programming, like memory management and pointer arithmetic. Python makes writing and reading code easier as it has its own garbage collector and can reduce the time needed to develop and maintain software.
  5. Open Source: ūüÜď Python is a language anyone can use, change, and give away for free. Many developers like to use it because they can make it work just how they want it to.
  6. Interpreted Language:ūüíĽ ¬† Python is an interpreted language that can run directly from the source code without compiling. This makes writing, testing, and debugging code easy and can speed up the development process.
  7. Python has multiple libraries, frameworks, and packages:ūüďö Python includes numerous amount of libraries that can be used just by importing. A number of popular and powerful Python libraries are available, including NumPy and Pandas for Data Science, Matplotlib and Seaborn for Data Visualization, and sklearn, Keras, PyTorch, etc., for Machine Learning.

How Python is used in different Industries

Python is used in industry for a variety of applications, as versatile and easy to use. Here are some of the most common ways that Python is used in industry:

  1. Web development: ūüĆé Python is a popular language for web development thanks to his Django and Flask, and other frameworks that are mostly used for web development. These frameworks provide an easy and efficient way to build web applications and websites.
  2. Data Science: ūüďä Python is widely used in data science for tasks such as data cleaning, data analysis, visualization, and ml modeling. Libraries like NumPy, Pandas, sklearn, seaborn and Matplotlib are commonly used for these tasks.
  3. Machine Learning: For machine learning Python is a popular language, thanks to libraries such as sklearn, TensorFlow, Keras, and PyTorch. These libraries provide a simple and efficient way to build and train machine learning models.
  4. Scientific Computing: ūüĒ¨ Python is widely used in scientific computing for tasks such as simulation and modeling. The SciPy library provides a wide range of tools for scientific computing. SciPy contains modules for optimization, linear algebra, integration, interpolation, special functions, etc.
  5. Automation and Scripting: ūüߨ Python is commonly used for automation and scripting tasks, such as automating workflows, system administration, and scripting repetitive tasks.
  6. Game Development: ūüéģ Python is used in game development for tasks such as scripting game logic and building game engines.
  7. Desktop Applications: ūüíĽ Python is also used for building desktop applications, thanks to frameworks such as PyQt and wxPython.

Advantages of Python

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Python is widely used because:

  • It is easier to read ūüďĖ, write ‚úćÔłŹ, and has shorter code ūüíĽ compared to languages like C++ or Java.
  • It supports multiple programming paradigms , including object-oriented ‚≠ē, imperative ūüďĆ, functional, and procedural programming.
  • It has extensive support libraries ūüďö such as Django ūüēłÔłŹ for web development and Pandas ūüźľ for data analytics.
  • It is a dynamically typed language , meaning that the data type is based on the value assigned.
  • It follows the philosophy that "simplicity is the best" ‚ú®.

CONCLUSION

Python is usually versatile , and very easy to learn and it is a widely-used programming language that is ideal for beginners. It’s simple-to-use, easy-to-learn, readability, and versatility make it a popular choice for a wide range of applications, from web development to data science to machine learning it is used mostly.

Key takeaways

  • Python is easy to learn, versatile, and has a large community of developers ūüĎ•.
  • Python is considered as a high-level language that abstracts away many of the low-level details of computer programming, making code easier to write ūüďĚ and read ūüďĖ.
  • Python is considered as an open-source language ūüÜď which is free for anyone to use, modify and distribute.
  • Python is considered as an interpreted language. This means that it can be run directly from the source code without compiling.
  • Python has numerous libraries ūüďö, frameworks, and packages, which are very popular with many developers
  • Python is widely used in industry for a variety of applications, including web development ūüĆź, data science ūüďä, machine learning, scientific computing, automation and scripting, game development ūüéģ, desktop applications, and more.
  • Mostly Python is used in industry, web development ūüĆź, data science ūüďä, machine learning, scientific computing, automation and scripting, and game development ūüéģ, and desktop applications.

QUIZ

  1. What is Python? 
    1. A low-level programming language
    2. A high-level programming language 
    3. A hardware language 
    4. A markup language

Answer: b. A high-level programming language

  1. Who created Python and when was it first released? 
    1. Created by Bill Gates in 1989 
    2. Created by Steve Jobs in 1991 
    3. In the late 1980s and first released in 1991 was created by Guido van Rossum in 
    4. Created by Mark Zuckerberg in 2004

Answer: c. Created by Guido van Rossum in the late 1980s and first released in 1991

  1. Why is Python easy to learn?
    1. It is a low-level language
    2. It has a complex syntax 
    3. It is known for its simplicity and readability 
    4. It is difficult to read and understand

Answer: c. It is known for its simplicity and readability

  1. What are some popular Python libraries used in data science? 
    1. NumPy and Pandas 
    2. Photoshop and Illustrator 
    3. Final Cut Pro and Premiere Pro 
    4. HTML and CSS

Answer: a. NumPy and Pandas

  1. What is one advantage of Python being an interpreted language? 
    1. It is difficult to write and test code 
    2. It requires compilation before running 
    3. It can be run directly from the source code without the need for compilation 
    4. It cannot be used for automation and scripting tasks

Answer: c. It can be run directly from the source code without the need for compilation

  1. What are some popular Python libraries used in machine learning? 
    1. Django and Flask 
    2. TensorFlow, Keras, and PyTorch 
    3. NumPy and Pandas 
    4. PyQt and wxPython

Answer: b. TensorFlow, Keras, and PyTorch

Module 1: Getting Started with Python Introduction to Python Programming

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