# How to Run Jupyter Notebooks in the AI for Beginners Project: A Complete Setup Guide

> Learn to run Jupyter notebooks for the AI for Beginners project. Follow this guide to clone the repo, set up Conda, install Jupyter, and launch the notebook server for your AI learning journey.

- Repository: [Microsoft/AI-For-Beginners](https://github.com/microsoft/AI-For-Beginners)
- Tags: how-to-guide
- Published: 2026-08-22

---

**To run the Jupyter notebooks in Microsoft's AI for Beginners course, clone the repository using either a full or sparse checkout, create a Conda environment from the provided [`environment.yml`](https://github.com/microsoft/AI-For-Beginners/blob/main/environment.yml), install Jupyter, and launch the server with `jupyter notebook`.**

The microsoft/AI-For-Beginners repository delivers a comprehensive, hands-on curriculum for artificial intelligence fundamentals through interactive Jupyter notebooks. To run these notebooks locally, you need to configure a Python environment with the specific dependencies defined in the project's configuration files. This guide walks you through the exact steps to clone the repository, set up your environment, and start exploring the lessons.

## Clone the Repository (Full vs. Sparse Checkout)

The README at the repository root offers two methods for obtaining the codebase. The full clone downloads all 50+ translation files, while the **sparse checkout** skips these large folders for a faster, leaner download.

### Full Clone Option

If you want the complete repository including all translations, use the standard clone command:

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

```

### Sparse Checkout (Recommended)

For beginners who want to save disk space and download time, Microsoft recommends a sparse checkout that excludes the translation directories:

```bash
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'

```

## Set Up the Python Environment

The project includes an [`environment.yml`](https://github.com/microsoft/AI-For-Beginners/blob/main/environment.yml) file that pins all required packages, including Jupyter, PyTorch, OpenCV, and scientific computing libraries.

### Using Conda (Recommended)

Create and activate the environment using the provided configuration:

```bash
conda env create -f environment.yml
conda activate ai4beg

```

### Using pip and virtualenv

If you prefer pip, install the dependencies listed in [`requirements.txt`](https://github.com/microsoft/AI-For-Beginners/blob/main/requirements.txt):

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

pip install -r requirements.txt

```

## Install and Launch Jupyter

While the Conda environment includes Jupyter, verify installation or add it manually if using pip.

### Installing Jupyter

```bash
pip install notebook   # Or: conda install notebook

```

### Starting the Server

Launch Jupyter from the repository root. The server will start a local web server and print a URL to your terminal:

```bash
jupyter notebook

```

For a more modern interface, use **JupyterLab**:

```bash
jupyter lab

```

## Navigate and Run Lesson Notebooks

Once the browser opens, navigate to the `lessons/` directory to access the curriculum. Each module contains interactive `.ipynb` files with executable code and explanations.

For example, to study the Perceptron implementation, open:

```

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

```

Or to explore convolutional neural networks:

```

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

```

Each lesson directory includes a README describing learning objectives and any required dataset downloads. The [`lessons/0-course-setup/how-to-run.md`](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/0-course-setup/how-to-run.md) file provides additional guidance specific to the development environment.

## Troubleshooting Common Issues

If you encounter errors launching notebooks, consult [`troubleshoot.md`](https://github.com/microsoft/AI-For-Beginners/blob/main/troubleshoot.md) in the repository root. This document addresses common problems such as missing Jupyter installations, kernel connection failures, and package version conflicts. The troubleshooting guide specifically recommends verifying your Jupyter installation with `pip install notebook` if the command is not found.

## Summary

- Clone the repository using either a full clone or a sparse checkout to exclude translations and save space.
- Create the Python environment using `conda env create -f environment.yml` or manually install packages via `pip install -r requirements.txt`.
- Install Jupyter Notebook or JupyterLab using pip or conda.
- Launch the server with `jupyter notebook` and navigate to specific lesson files in the `lessons/` directory.
- Reference [`troubleshoot.md`](https://github.com/microsoft/AI-For-Beginners/blob/main/troubleshoot.md) for solutions to common setup issues.

## Frequently Asked Questions

### Do I need a GPU to run the notebooks?

No, the majority of the AI for Beginners notebooks run comfortably on CPU-only machines. While some deep learning lessons in `lessons/4-ComputerVision/` may train faster with GPU acceleration, the code defaults to CPU execution and includes fallbacks for systems without CUDA.

### Can I run these notebooks in Google Colab?

Yes, you can upload the `.ipynb` files to Google Colab or Azure Notebooks. However, you may need to manually install dependencies listed in [`requirements.txt`](https://github.com/microsoft/AI-For-Beginners/blob/main/requirements.txt) at the start of each session, as the cloud environments do not automatically load the course's Conda environment.

### What if Jupyter doesn't open in my browser?

If the terminal shows the server URL but your browser doesn't launch automatically, copy the URL (typically `http://localhost:8888/` with a token) and paste it manually into your browser. Ensure no firewall is blocking the local port, and check [`troubleshoot.md`](https://github.com/microsoft/AI-For-Beginners/blob/main/troubleshoot.md) for platform-specific browser integration issues.

### How do I update the environment when the course changes?

When the repository updates, pull the latest changes and update your environment. For Conda users, run `conda env update -f environment.yml` after pulling. For pip users, run `pip install -r requirements.txt --upgrade` to refresh the package versions.