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Week 1-2 : First two days of your Python learning journey:

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Day 1: Introduction to Python

  • Start by understanding what Python is:
  • Python is a high-level, interpreted programming language known for its readability and versatility.
  • It is widely used in web development, data science, machine learning, scientific computing, and more.
  • Explore Python’s characteristics:
  • Readability and clean syntax make it easy for beginners.
  • It is dynamically typed, meaning you don’t need to declare variable types explicitly.
  • Python has a large standard library with pre-built modules for various tasks.
  • Learn about Python 2 vs. Python 3:
  • Python 2 is legacy and no longer supported; focus on Python 3, which is the current version (e.g., Python 3.7, 3.8, 3.9, etc.).
  • Install Python:
  • Visit the official Python website (https://www.python.org/) to download the latest Python version for your operating system (Windows, macOS, Linux).
  • Installation steps for Windows:
  • Run the installer.
  • Check the box that says “Add Python X.X to PATH” during installation.
  • Click “Install Now.”
  • Installation steps for macOS:
  • Run the installer package.
  • Follow the installation instructions.
  • Installation steps for Linux:
  • Open a terminal.
  • Use your package manager to install Python (e.g., sudo apt-get install python3 for Debian/Ubuntu).
  • Verify the installation by opening a terminal and typing python3. You should see the Python interpreter prompt.

Day 2: Installing an IDE (e.g., Anaconda, Jupyter Notebook, or Visual Studio Code)

  • Understand what an Integrated Development Environment (IDE) is:
  • An IDE is a software application that provides a comprehensive environment for writing, debugging, and running code.
  • Explore different Python IDE options:
  • Anaconda: A Python distribution that includes Python, Jupyter Notebook, and popular data science libraries. Great for data science and scientific computing.
  • Jupyter Notebook: An interactive web-based environment for data analysis and visualization. Often used for data science and educational purposes.
  • Visual Studio Code (VS Code): A highly customizable, free, and open-source code editor with Python support. Suitable for a wide range of Python projects.
  • Installation steps for Anaconda (if you choose this option):
  • Download the Anaconda installer for your OS from the Anaconda website (https://www.anaconda.com/products/individual).
  • Run the installer and follow the installation instructions.
  • Anaconda includes Python, Jupyter Notebook, and various data science libraries.
  • Installation steps for Jupyter Notebook (if you choose this option):
  • If you’ve installed Anaconda, Jupyter Notebook is already available.
  • Otherwise, you can install it using pip: pip install notebook.
  • Installation steps for Visual Studio Code (if you choose this option):
  • Download the Visual Studio Code installer for your OS from the VS Code website (https://code.visualstudio.com/).
  • Run the installer and follow the installation instructions.
  • Install the “Python” extension within VS Code for enhanced Python support.
  • Launch your chosen IDE and create your first Python script:
  • In Anaconda or Jupyter Notebook, open a new Jupyter Notebook or create a Python script.
  • In Visual Studio Code, open a new Python file (.py) and start writing code.

By the end of Day 2, you should have Python installed and be ready to start coding in your chosen IDE.