Chapter 1 | Setup Guide for Windows and Mac | AI Engineer Course for beginner

This guide covers Python, VS Code, Git, UV, API keys, and Qdrant Cloud.

Cost: Free to get started
Supported OS: Windows and macOS

1. Install Python 3.11

Windows

1. Download Python 3.11.9.

2. Run the Windows 64-bit installer.

3. Check Add python.exe to PATH.

4. Click Install Now.

5. Verify the installation:

python --version

Expected output: Python 3.11.9

macOS

Install Homebrew if you don't already have it:

/bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)"

For Apple Silicon Macs, configure Homebrew if required:

echo 'eval "$(/opt/homebrew/bin/brew shellenv)"' >> ~/.zprofile
eval "$(/opt/homebrew/bin/brew shellenv)"

Install Python:

brew install python@3.11

Verify:

python3.11 --version

2. Install Visual Studio Code

Download Visual Studio Code.

• Windows: Run the installer and enable the recommended options, including adding VS Code to PATH.

• macOS: Download the archive, extract it, and move Visual Studio Code to Applications. Open VS Code, press Cmd + Shift + P, and select Shell Command: Install 'code' command in PATH.

Install these Microsoft extensions:

• Python

• Pylance

• Jupyter

3. Install Git

Git helps you track code changes and manage your course projects.

Windows

Download and install Git for Windows. The default installation options are sufficient.

macOS

brew install git

Configure Git

Run these commands on either operating system:

git --version

git config --global user.name "Your Name"
git config --global user.email "your@email.com"

Replace the example name and email with your own details.

4. Install UV

UV is a fast Python package and project manager that we'll use throughout the course.

Windows

Open PowerShell and run:

powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"

If PowerShell blocks the script, run:

Set-ExecutionPolicy RemoteSigned -Scope CurrentUser

Reopen the terminal after installation.

macOS

curl -LsSf https://astral.sh/uv/install.sh | sh

Reopen the terminal after installation.

Verify UV

uv --version

5. Install Windows Terminal

Windows users only: Install Windows Terminal from the Microsoft Store.

Pin it to your taskbar for convenient access to PowerShell and other command-line tools.

macOS users can use the built-in Terminal application.

6. Create a GitHub Account

Create a free account at GitHub.

1. Enter your email and create a password.

2. Choose a professional username.

3. Verify your email address.

4. Select the Free plan.

5. Add a profile photo and a short bio.

We'll use GitHub to store and manage course projects.

7. Get Your AI API Keys

You'll configure three LLM providers and one vector database for the course.

Groq API — Primary LLM

1. Visit Groq Console.

2. Sign in.

3. Open API Keys.

4. Create a key named padho-course.

5. Copy and securely store the key.

Gemini API — Backup LLM

1. Visit Google AI Studio.

2. Sign in with Google.

3. Select Get API key.

4. Create a key in a new project.

5. Copy and securely store the key.

OpenRouter — Access to Multiple Models

1. Visit OpenRouter.

2. Sign in with Google or GitHub.

3. Open your profile and select Keys.

4. Create a key named padho-course.

5. Copy and securely store the key.

Qdrant Cloud — Vector Database

1. Visit Qdrant Cloud.

2. Sign in with Google or GitHub.

3. Open Clusters and create a cluster.

4. Select the Free tier, if available.

5. Choose AWS Mumbai (ap-south-1) if available.

6. Name the cluster padho-course.

7. Wait for provisioning to finish.

8. Copy the cluster URL and API key.

Note: Free-tier limits, available regions, and API usage quotas may change. Check each provider's current pricing and limits before using it.

8. Create Your Environment Variables File

Create a project directory named padho-ai-engineer and add a .env file to store your API credentials.

Windows

Open Windows Terminal and run:

cd $HOME
mkdir padho-ai-engineer
cd padho-ai-engineer
notepad .env

macOS

Open Terminal and run:

cd ~
mkdir padho-ai-engineer
cd padho-ai-engineer
touch .env
open -a TextEdit .env

Add Your API Keys

Paste the following into the .env file and replace the placeholders with your actual credentials:

GROQ_API_KEY=gsk_your_key_here
GOOGLE_API_KEY=AIza_your_key_here
OPENROUTER_API_KEY=sk-or-your_key_here
QDRANT_URL=https://xxxxx.aws.cloud.qdrant.io
QDRANT_API_KEY=your_qdrant_key_here

Save the file.

Security rule: Never commit your .env file to GitHub. Add it to .gitignore before making your first commit.

Create a .gitignore file containing:

.env
.venv/
__pycache__/

Keep your API keys private and never paste them into public repositories.

9. Create Your Course Folder Structure

We'll organize the 8-week course into separate folders.

Windows

Run this command inside padho-ai-engineer:

1..8 | ForEach-Object { New-Item -ItemType Directory -Name "week$_" }

macOS

mkdir week{1..8}

Open the project in VS Code:

code .

Your folder structure should look like this:

padho-ai-engineer/
├── .env
├── .gitignore
├── week1/
├── week2/
├── week3/
├── week4/
├── week5/
├── week6/
├── week7/
└── week8/

10. Verify Your Setup

Run the following commands in your terminal.

Windows

python --version
uv --version
git --version
code --version

macOS

python3.11 --version
uv --version
git --version
code --version
brew --version

Make sure each command returns a version number. UV, Git, VS Code, and Homebrew version numbers may differ from the examples because they receive updates.

11. Troubleshooting Common Problems

Conclusion

Your development environment is now ready for the 8-week AI Engineer course.

Before starting Day 1, confirm that Python, UV, Git, and VS Code work correctly and that your API credentials are stored securely.

Next step: Open the padho-ai-engineer project in VS Code and get ready to build your first AI application.