# How to Clone the Microsoft AI For Beginners Repository: Complete Guide with Sparse Checkout

> Learn to clone the Microsoft AI For Beginners repository efficiently. Use sparse checkout to download only core curriculum and skip translation folders for a faster setup.

- Repository: [Microsoft/AI-For-Beginners](https://github.com/microsoft/AI-For-Beginners)
- Tags: how-to-guide
- Published: 2026-08-01

---

**To clone the Microsoft AI For Beginners repository, use either a standard `git clone` for everything or a sparse-checkout clone to download only the core curriculum while skipping 50+ translation folders.**

The AI For Beginners repository from Microsoft is a comprehensive machine learning curriculum containing notebooks, labs, and educational materials spread across many directories. However, its size—including over 50 language translation folders and binary assets—makes a full clone unnecessarily heavy for most learners. This guide shows you two methods to **clone AI For Beginners**, from the full download to the recommended lightweight approach.

## Standard Clone: Get Everything Including Translations

If you need access to all translations and every file in the curriculum, perform a regular clone:

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

```

This downloads the complete repository including `translations/`, `translated_images/`, `lessons/`, `examples/`, and all other directories. Expect larger download times and disk usage.

## Sparse-Checkout Clone: Recommended for Most Learners (Faster)

The **preferred method** documented in the repository's [[`README.md`](https://github.com/microsoft/AI-For-Beginners/blob/main/README.md)](https://github.com/microsoft/AI-For-Beginners/blob/main/README.md) uses Git's partial clone and sparse-checkout features. This fetches only the `lessons/` folder and core files while excluding heavy translation directories.

### Linux/macOS Commands

```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'

```

### Windows CMD Commands

```cmd
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"

```

### What These Flags Do

| Flag | Purpose |
|------|---------|
| `--filter=blob:none` | Enables partial clone; delays downloading file contents until needed |
| `--sparse` | Initializes sparse-checkout mode immediately |
| `--no-cone` | Uses full pattern matching instead of cone mode for precise exclusions |
| `'/*'` | Includes all top-level files and directories |
| `'!translations'` `'!translated_images'` | Excludes these specific directories from checkout |

This approach dramatically reduces initial download size while preserving full functionality for running the curriculum locally.

## Setting Up Your Environment After Cloning

Once you've cloned AI For Beginners, configure the Python environment using the provided [[`environment.yml`](https://github.com/microsoft/AI-For-Beginners/blob/main/environment.yml)](https://github.com/microsoft/AI-For-Beginners/blob/main/environment.yml):

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

```

For detailed environment setup instructions, see [[`lessons/0-course-setup/setup.md`](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/0-course-setup/setup.md)](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/0-course-setup/setup.md).

## Key Files and Directories

| Path | Description |
|------|-------------|
| `lessons/` | Core curriculum notebooks and labs |
| `examples/` | Quick-start code samples including Hello AI World and Simple Neural Network |
| `etc/quiz-app/` | Vue.js quiz application for testing knowledge |
| [`environment.yml`](https://github.com/microsoft/AI-For-Beginners/blob/main/environment.yml) | Conda environment with all dependencies |

## Summary

- **Standard `git clone`** downloads everything including translations—use only if you need multilingual content.
- **Sparse-checkout clone** is the recommended way to **clone AI For Beginners** efficiently—it skips `translations/` and `translated_images/` while keeping all functional curriculum materials.
- Both methods use the same repository URL: `https://github.com/microsoft/AI-For-Beginners.git`
- After cloning, activate the conda environment from [`environment.yml`](https://github.com/microsoft/AI-For-Beginners/blob/main/environment.yml) and launch Jupyter to begin learning.

## Frequently Asked Questions

### Do I need the translations folder to complete the course?

No. The `translations/` directory contains localized versions of README files in 50+ languages. The core curriculum in `lessons/` including all Jupyter notebooks, code, and exercises is fully functional without translations. The sparse-checkout method documented in the repository's [`README.md`](https://github.com/microsoft/AI-For-Beginners/blob/main/README.md) is specifically designed for learners who want English or prefer faster setup.

### Why is my git clone taking so long for AI For Beginners?

The repository exceeds several gigabytes when fully cloned due to accumulated translation assets and binary files. Use the `--filter=blob:none --sparse` approach to reduce initial download to a fraction of the size. Git will fetch additional content on-demand only when you access specific files.

### Can I add translations back after a sparse-checkout clone?

Yes. Run `git sparse-checkout set --no-cone '/*'` inside the repository to include all directories, or selectively add `translations` with `git sparse-checkout add translations`. The partial clone remains efficient—content downloads only when you actually check out those paths.

### What Git version do I need for sparse checkout?

Git 2.25 or later supports `--sparse` and `sparse-checkout` commands. Check your version with `git --version`. The `--filter=blob:none` partial clone feature requires Git 2.22+. Most modern Git installations meet these requirements.