Prerequisites

This document outlines the prerequisites for diving into the AI and Machine Learning learning paths. It covers essential concepts, tools, and techniques that you should be familiar with before starting your journey.

Before diving into AI and Machine Learning, ensure you have a solid understanding of the following concepts:

• Python and pip package management: Familiarity with Python programming and how to manage packages using pip is essential for working with various libraries and frameworks in AI and Machine Learning.

• Google Colab or Jupyter Notebooks: These tools are commonly used for interactive coding and data analysis. They allow you to write and execute Python code in a web-based environment, making it easier to visualize data and share your work with others.

Info

I recommend using Google Colab for its ease of use and accessibility. One doesnt need to install anything locally, and it provides free access to GPUs for training models. However, if you prefer a local setup, Jupyter Notebooks is a great alternative.

Local Setup

1. Python Installation: Ensure you have Python installed on your local machine. You can download it from the official Python website. Make sure to install pip, which is included with Python installations.

2. Visual Studio Code: Download and install Visual Studio Code, a popular code editor that supports Python development. Install the Python Data Science ExtensionPack.
   You will be able to run Jupyter Notebooks directly in VS Code, which is a great feature for data science projects.