# How to Navigate the AI-For-Beginners Repository: Complete Structure Guide

> Master the AI-For-Beginners repository structure. Discover lessons, notebooks, labs, and the quiz app in this comprehensive guide to Microsoft's AI curriculum.

- Repository: [Microsoft/AI-For-Beginners](https://github.com/microsoft/AI-For-Beginners)
- Tags: how-to-guide
- Published: 2026-08-24

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**The AI-For-Beginners repository organizes a 12-week curriculum into thematic lesson folders containing READMEs, executable Jupyter notebooks, and supplemental labs, with a Vue-based quiz application located in `etc/quiz-app` and environment configuration files at the repository root.**

The **AI-For-Beginners** repository from Microsoft provides a comprehensive open-source curriculum for learning artificial intelligence concepts. To navigate the AI-For-Beginners repository effectively, you need to understand its hierarchical structure that separates lessons by topic, houses executable code in framework-specific notebooks, and includes interactive assessment tools. This guide maps every critical directory and file path to help you locate lessons, configure your environment, and run the course materials without friction.

## Repository Structure Overview

The repository root contains the master index and environment definitions, while the `lessons/` directory houses the curriculum content.

### Root-Level Files

- **[`README.md`](https://github.com/microsoft/AI-For-Beginners/blob/main/README.md)** – The primary entry point containing the table of contents, setup instructions, and quick links to every lesson beginning at line 81.
- **[`environment.yml`](https://github.com/microsoft/AI-For-Beginners/blob/main/environment.yml)** – Conda environment specification including TensorFlow, PyTorch, OpenCV, and other dependencies required for the notebooks.
- **[`requirements.txt`](https://github.com/microsoft/AI-For-Beginners/blob/main/requirements.txt)** – Alternative pip-based dependency list for Binder deployments.
- **[`.devcontainer/devcontainer.json`](https://github.com/microsoft/AI-For-Beginners/blob/main/.devcontainer/devcontainer.json)** – VS Code dev-container configuration for a ready-to-run development environment.
- **[`CONTRIBUTING.md`](https://github.com/microsoft/AI-For-Beginners/blob/main/CONTRIBUTING.md)** – Guidelines for submitting pull requests and contribution standards.

### The Lessons Directory

The curriculum resides in `lessons/` and follows a 12-week structure split into thematic folders:

- **`0-course-setup/`** – Installation and configuration guides.
- **`1-Intro/`** through **`7-Ethics/`** – Core curriculum topics including Symbolic AI, Neural Networks, Computer Vision, NLP, and AI Ethics.
- **`X-Extras/`** – Supplementary materials and advanced topics.

Each thematic folder contains numbered subdirectories (e.g., `07-ConvNets/`) that include:
- A [`README.md`](https://github.com/microsoft/AI-For-Beginners/blob/main/README.md) describing the concept and linking to resources.
- Executable `.ipynb` notebooks for **PyTorch**, **TensorFlow**, and **Keras**.
- An optional `lab/` subdirectory with hands-on exercises.

## Navigating the Curriculum Step-by-Step

To locate and launch specific lessons, follow this navigation path as implemented in the Microsoft AI-For-Beginners repository:

1. **Start at the Root README** – Lines 24-30 list supported translations, while the table beginning at line 81 maps every lesson to its associated files.

2. **Select a Theme** – Open a thematic index like [`lessons/4-ComputerVision/README.md`](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/4-ComputerVision/README.md) to view lessons within that category.

3. **Open a Specific Lesson** – Enter a numbered folder (e.g., `lessons/4-ComputerVision/07-ConvNets/`) and consult its [`README.md`](https://github.com/microsoft/AI-For-Beginners/blob/main/README.md) for concept explanations and notebook links.

4. **Launch the Notebook** – Choose your preferred framework version (e.g., `ConvNetsPyTorch.ipynb` or `ConvNetsTensorflow.ipynb`) and open it in Jupyter Lab.

## Running the Jupyter Notebooks

Before executing code, activate the Conda environment defined in [`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

```

Navigate to your target notebook within the `lessons/` hierarchy. For example, open `lessons/3-NeuralNetworks/05-Frameworks/IntroPyTorch.ipynb` to execute PyTorch fundamentals, or `lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb` for transformer-based BERT tutorials. Each notebook combines theoretical explanations with executable code cells and inline visualizations.

## Working with Labs and Exercises

Many lessons include supplemental reinforcement activities in `lab/` subdirectories. After completing a lesson's notebook:

- Locate the [`lab/README.md`](https://github.com/microsoft/AI-For-Beginners/blob/main/lab/README.md) inside the lesson folder (e.g., [`lessons/4-ComputerVision/07-ConvNets/lab/README.md`](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/4-ComputerVision/07-ConvNets/lab/README.md)).
- Follow the project instructions to apply concepts to practical scenarios.
- Check solutions or hints if provided in the lab directory.

## Launching the Quiz Application

The interactive assessment tool lives under `etc/quiz-app/` and runs as a Vue 2.x single-page application. To serve it locally:

```bash
cd etc/quiz-app
npm install
npm run serve

```

This starts a development server at `http://localhost:8080`. To create a production build, run `npm run build`, which generates static files in `etc/quiz-app/dist/`. The quiz content synchronizes with the lesson materials, allowing immediate knowledge testing after completing modules.

## Multi-Language Support

The repository includes over 50 language packs stored in `translations/`. Each locale maintains its own [`README.md`](https://github.com/microsoft/AI-For-Beginners/blob/main/README.md) (e.g., [`translations/zh-TW/README.md`](https://github.com/microsoft/AI-For-Beginners/blob/main/translations/zh-TW/README.md) for Traditional Chinese). The root [`README.md`](https://github.com/microsoft/AI-For-Beginners/blob/main/README.md) table at lines 24-30 provides direct links to every supported translation, ensuring accessibility for non-English learners.

## Summary

- The **root [`README.md`](https://github.com/microsoft/AI-For-Beginners/blob/main/README.md)** serves as the master index with links to all 12 weeks of content.
- **Lesson packages** reside in `lessons/` with numbered subdirectories containing framework-specific notebooks and [`README.md`](https://github.com/microsoft/AI-For-Beginners/blob/main/README.md) explanations.
- **Labs** in `lab/` subdirectories provide hands-on practice for reinforcing concepts.
- The **Vue quiz app** in `etc/quiz-app` offers interactive assessment via `npm run serve`.
- **Environment setup** uses [`environment.yml`](https://github.com/microsoft/AI-For-Beginners/blob/main/environment.yml) (Conda) or [`.devcontainer/devcontainer.json`](https://github.com/microsoft/AI-For-Beginners/blob/main/.devcontainer/devcontainer.json) (VS Code containers).
- **Translations** are maintained in `translations/<lang>/` with the root README linking to over 50 localized versions.

## Frequently Asked Questions

### How do I find the setup instructions for the AI-For-Beginners repository?

The complete setup guide resides in [`lessons/0-course-setup/setup.md`](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/0-course-setup/setup.md), which provides first-time installation instructions for the entire curriculum. Alternatively, the root [`README.md`](https://github.com/microsoft/AI-For-Beginners/blob/main/README.md) contains quick-start steps, and the [`environment.yml`](https://github.com/microsoft/AI-For-Beginners/blob/main/environment.yml) file defines all required Python packages including TensorFlow and PyTorch versions.

### Where are the executable code examples located?

Practical code examples exist as Jupyter notebooks within each lesson's numbered folder. For instance, `lessons/4-ComputerVision/07-ConvNets/ConvNetsPyTorch.ipynb` contains the PyTorch implementation of convolutional networks. Each lesson typically offers multiple framework versions (PyTorch, TensorFlow, Keras) in the same directory.

### Can I run the course materials without installing Python locally?

Yes. The repository includes a [`.devcontainer/devcontainer.json`](https://github.com/microsoft/AI-For-Beginners/blob/main/.devcontainer/devcontainer.json) configuration that enables VS Code's remote containers extension, providing a pre-configured environment with all dependencies. Alternatively, the [`requirements.txt`](https://github.com/microsoft/AI-For-Beginners/blob/main/requirements.txt) file supports Binder deployments for browser-based execution without local installation.

### How do I access the course content in my native language?

Navigate to the `translations/` directory and select your language code (e.g., `zh-TW` for Traditional Chinese, `es` for Spanish). Each folder contains a localized [`README.md`](https://github.com/microsoft/AI-For-Beginners/blob/main/README.md). The root [`README.md`](https://github.com/microsoft/AI-For-Beginners/blob/main/README.md) table (lines 24-30) provides direct links to over 50 supported languages, allowing you to browse the curriculum in your preferred locale.