Day 1 - Web Dev to AI Engineer : Hello AI World

PHP/CodeIgniter to Artificial Intelligence - join me on my journey to become an AI Engineer.

My journey will be in 5 phases (The Roadmap).

• Phase 1 - AI Engineer Foundation
  In this phase the goal is to learn Python fluently and get into the AI Engineering mindset.

• Phase 2 - Machine Learning Kickstart
  In this phase the goal is to learn the core ML concepts and build some learning projects.

• Phase 3 - Deep Learning & NLP Basics
  In this phase the goal is to learn to build AI-powered apps chat-bots, translators and more.

• Phase 4 - Data Engineering + Real World AI Apps
  In this phase the goal is to learn how AI engineers work in production.

• Phase 5 - Capstone Projects
  In this the goal is to build professional real world app and ship it out in the world.

Phase 1 : Day -1

Focus: Environment Setup and First Steps in Python

As an experienced web developer, transitioning into AI feels exciting but sometimes a bit scary.

Today, I started Phase 1 of my Roadmap to becoming an AI Engineer.

What I Did

Installed My AI Dev Stack

1. Python 3.12.2
   I downloaded the Python from its website and installed it on my laptop.

   

2. Visual Studio Code extensions - Python & Jupyter
   I have been using VS Code for several years now. You can download it for free from its website and install it.

   

   After installing VS Code, open the application. Then go to View > Extensions option.

   

   In the Extensions sidebar search box, lets type Python. When the extension appears, click Install button. Similarly we can install Jupyter extension.

   

   

   Note: When you first run a Jupyter notebook, VS Code will ask for your permission to install the ipykernel package before running it.

   

   

3. Virtual Environment
   It is a Python environment, that is self-contained directory which includes.

   • A Python interpreter

   • Set of installed package/libraries

   • Their versions of packages/libraries can differ for different projects

   • It is a Python environment, that is self-contained directory which includes.

     Create using venv (recommended)
     Step 1: Check if Python is installed
     Run the following command to verify that Python is installed:
     python --version

     python3 --version (for mac)

We need to make sure the Python version is 3.6 or higher.

Step 2: Create a Virtual Environment
Run the following command in your project folder:
python -m venv <env name>

python3 -m venv <env name> (for mac)

In the screenshot above, you can see a folder in the left panel with the same name as your virtual environment.

Step 3: Activate the Virtual Environment
In Windows CMD or Powershell
<env name>\Scripts\activate
In Mac/Linux
source <env name>/bin/activate

When the environment is activated, you will see the environment name in brackets (refer to the screenshot above).

Step 4: Install Required Packages
Once the environment is activated, you can install dependencies using the following command.
pip install package_name
Example:
pip install panda numpy

Step 5: List Installed Packages
To view all the installed packages in the virtual environment
pip list

Step 6: Deactivate the Environment
To exit the virtual environment when done
deactivate

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My First Notebook

In VS Code, go to File > New File and create a new file with the .ipynb extension.

print("Hello World")

After typing the code, press Ctrl + Enter to display the result.

Seeing the message felt more exciting than Hello World ever did. This is the first line of code in a journey.

Reflection

Setting up may not be glamorous, but it’s the runway to liftoff. Every great AI project starts with the right tools in place.

What’s Next

• Python Core - Basic syntax, Data types, Operators, Conditional Statements, Loops