Introduction

Generative AI refers to AI systems designed to create new content, such as text, images, music, code, or even video, using patterns learned from existing data. It's powered by advanced machine learning models like GPT (text generation), DALL·E (image generation), Stable Diffusion, etc.

Why you should learn Generative AI?

High Demand: Generative AI is transforming industries like content creation, marketing, healthcare, and entertainment.
Innovation Potential: Enables automation and creation of innovative solutions, such as chatbots, creative tools, and personalized experiences.
Career Growth: Expertise in AI, especially generative models, is highly sought after in fields like tech, research, and business.
Creative Empowerment: Offers tools to enhance creativity by automating repetitive tasks or creating entirely new outputs.
Future-Ready Skills: Generative AI is foundational to emerging technologies like the Metaverse, virtual assistants, and AI art.

Environment Setup
For this learning journey, I will be using Conda as the base for my environment setup. My reasons are as follows: Using Conda has several advantages, especially for managing Python environments and dependencies in data science and AI projects, including Generative AI.

Step 1: Download Anaconda
Step 2: Follow the instruction to install Anaconda on your system depending on your operating system

Step 3: Verify installation

  conda --version

Step 4:

• Create a new environment for Generative AI:

conda create --name test_env python=3.9

• Activate the environment:

conda activate test_env

• Install essential AI libraries:

pip install torch transformers matplotlib

Set Up VS Code

Install Visual Studio Code Download.

• Add the Python Extension:
  • Go to the Extensions tab and search for "Python".
  • Install the extension by Microsoft.
  • Install the Jupyter extension in VS Code
• Select your Conda environment in VS Code:
• Open the Command Palette (Ctrl+Shift+P or Cmd+Shift+P).
• Search for "Python: Select Interpreter".