How to Run Jupyter Notebooks in the Microsoft AI for Beginners Course: Complete Setup Guide

Clone the AI-For-Beginners repository, create a conda environment from environment.yml, and launch Jupyter Notebook or JupyterLab to start the interactive lessons.

The Microsoft AI for Beginners curriculum is built entirely around interactive Jupyter notebooks. To run them, you need a working Python environment, the required dependencies specified in the project's configuration files, and the Jupyter server itself. This guide walks through the exact setup process using the source files in the microsoft/AI-For-Beginners repository.

Clone the Repository (Full or Sparse Checkout)

The README in the repository root provides two ways to obtain the codebase. A full clone pulls all 50+ translation files, while a sparse checkout skips those large folders for a faster download.

Option 1: Full Clone

git clone https://github.com/microsoft/AI-For-Beginners.git
cd AI-For-Beginners

Option 2: Sparse Checkout (Recommended)

This approach omits translation files and is significantly faster:

git clone --filter=blob:none --sparse https://github.com/microsoft/AI-For-Beginners.git
cd AI-For-Beginners
git sparse-checkout set --no-cone '/*' '!translations' '!translated_images'

The sparse checkout command is defined in README.md lines 31-40 according to the source analysis.

Create a Python Environment with Dependencies

The project ships an environment.yml file that lists all required packages, including Jupyter itself, ipykernel, ipywidgets, OpenCV, and PyTorch.

Using Conda (Recommended)

conda env create -f environment.yml
conda activate ai4beg

The environment.yml specifies these dependencies in lines 5-11.

Using Virtualenv + Pip

If you prefer pip-based installation, use the provided requirements.txt:

python -m venv venv
source venv/bin/activate   # Windows: venv\Scripts\activate

pip install -r requirements.txt

Both environment.yml and requirements.txt are located in the repository root.

Install Jupyter Notebook Server

If Jupyter is not already present in your environment, install it explicitly. The troubleshooting guide in troubleshoot.md (lines 79-99) provides the exact commands:

# Using pip

pip install notebook

# Or using conda

conda install notebook

For an enhanced interface, you can also install JupyterLab:

pip install jupyterlab

Launch Jupyter and Open Course Notebooks

Start the Jupyter server from the repository root. It will automatically open your default web browser, or you can copy the URL printed in the terminal.

# Classic Notebook interface

jupyter notebook

# Or JupyterLab (richer UI with file browser)

jupyter lab

Once the browser opens, navigate to the lessons/ folder and select any notebook. For example:

lessons/3-NeuralNetworks/03-Perceptron/Perceptron.ipynb

Each lesson also contains a README describing learning objectives and any required dataset downloads.

Complete Setup Command Sequence

Here is the full workflow from clone to running your first notebook:

# 1️⃣ Clone (sparse recommended) and enter repo

git clone --filter=blob:none --sparse https://github.com/microsoft/AI-For-Beginners.git
cd AI-For-Beginners
git sparse-checkout set --no-cone '/*' '!translations' '!translated_images'

# 2️⃣ Build the conda environment

conda env create -f environment.yml
conda activate ai4beg

# 3️⃣ Ensure Jupyter is installed

pip install notebook   # or: conda install notebook

# 4️⃣ Start the notebook server

jupyter notebook   # or: jupyter lab

# 5️⃣ In the browser, open lessons, for example:

# lessons/4-ComputerVision/07-ConvNets/ConvNetsPyTorch.ipynb

Key Configuration Files Reference

File	Purpose
environment.yml	Lists exact conda packages including Jupyter, PyTorch, OpenCV
requirements.txt	Pip-based dependency list for manual installations
lessons/0-course-setup/setup.md	Overview of required tools and quick-start steps
lessons/0-course-setup/how-to-run.md	Detailed Jupyter launch and navigation instructions
troubleshoot.md	Common issues (missing Jupyter, kernel errors) and fixes

Alternative: Run Notebooks in the Cloud

If local setup is not feasible, the AI for Beginners notebooks can also run on cloud platforms such as Google Colab or Azure Notebooks. Most notebooks include "Open in Colab" badges for direct execution without local installation.

Summary

• Clone the repository using standard git or a sparse checkout for faster download
• Create environment from environment.yml using conda or requirements.txt with pip
• Install Jupyter via pip install notebook or conda install notebook if not present
• Launch with jupyter notebook or jupyter lab from the repository root
• Navigate to lessons/ and select any .ipynb file to start learning

Frequently Asked Questions

What Python version does AI for Beginners require?

The environment.yml specifies Python 3.8 or later. Conda will automatically install a compatible version when you create the environment from that file.

Can I use pip instead of conda to run Jupyter notebooks in AI for Beginners?

Yes. While conda is recommended, you can create a virtual environment with python -m venv and install dependencies from requirements.txt. Then install Jupyter with pip install notebook and proceed with jupyter notebook.

Where are the actual lesson notebooks located in the repository?

All interactive notebooks are organized under lessons/ with subdirectories for each module. For example: lessons/3-NeuralNetworks/03-Perceptron/Perceptron.ipynb. The lessons/0-course-setup/how-to-run.md file provides additional navigation guidance.

What should I do if Jupyter fails to start or shows "command not found"?

Check troubleshoot.md lines 79-99 for specific fixes. Most commonly, Jupyter is not installed in your active environment. Run pip install notebook or conda install notebook, then ensure your environment is activated with conda activate ai4beg before launching.

{
  "mcpServers": {
    "instagit": {
      "command": "npx",
      "args": ["-y", "instagit@latest"]
    }
  }
}