# How to Get Started with Microsoft AI-For-Beginners: A Complete Setup Guide

> Start your AI journey with Microsoft AI-For-Beginners. Clone the repo, set up your Conda environment, and launch Jupyter Notebook to access beginner AI lessons.

- Repository: [Microsoft/AI-For-Beginners](https://github.com/microsoft/AI-For-Beginners)
- Tags: getting-started
- Published: 2026-08-11

---

**To get started with Microsoft AI-For-Beginners, clone the repository, create the Conda environment using [`.devcontainer/environment.yml`](https://github.com/microsoft/AI-For-Beginners/blob/main/.devcontainer/environment.yml), and launch Jupyter Notebook to begin with the setup lessons in `lessons/0-course-setup/`.**

The **AI-For-Beginners** repository by Microsoft is a comprehensive 12-week, 24-lesson open-source curriculum designed to teach artificial intelligence fundamentals through hands-on Jupyter notebooks, quizzes, and lab exercises. Whether you are learning about symbolic AI, neural networks, computer vision, or natural language processing, this project-based course provides all necessary materials in the `lessons/` directory, supplemented by runnable starter examples and an integrated Vue 2 quiz application.

## Repository Structure Overview

Understanding the layout of AI-For-Beginners helps you navigate the curriculum efficiently. The repository organizes content into distinct functional areas:

- **`lessons/`** – Contains the core 24-lesson curriculum, including README files for theory and `.ipynb` notebooks for practical exercises (covering symbolic AI, neural networks, computer vision, NLP, and ethics).
- **`examples/`** – Houses small, self-contained Python scripts like [`01-hello-ai-world.py`](https://github.com/microsoft/AI-For-Beginners/blob/main/01-hello-ai-world.py) for immediate hands-on experimentation before diving into full lessons.
- **`etc/quiz-app/`** – A Vue 2 application that serves interactive quizzes to reinforce concepts from each lesson.
- **`translations/`** – Supports 50+ languages, enabling non-English learners to follow the same material.
- **[`.devcontainer/environment.yml`](https://github.com/microsoft/AI-For-Beginners/blob/main/.devcontainer/environment.yml)** – Defines the reproducible Python stack including TensorFlow, PyTorch, Keras, OpenCV, NumPy, pandas, and Jupyter.
- **[`index.html`](https://github.com/microsoft/AI-For-Beginners/blob/main/index.html)** – Powers the Docsify-based documentation site for web-friendly curriculum browsing.

## Step 1: Clone the Repository

You can clone the full repository or use a sparse checkout to exclude large translation folders if you only need English content.

**Full clone:**

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

```

**Sparse checkout (excludes `translations/` and `translated_images/`):**

```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'

```

## Step 2: Configure the Python Environment

The repository provides a Conda environment definition that guarantees a consistent Python stack across all lessons. As documented in [`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), execute the following commands:

```bash
conda env create --name ai4beg --file .devcontainer/environment.yml
conda activate ai4beg

```

This installation includes TensorFlow, PyTorch, Keras, OpenCV, NumPy, pandas, matplotlib, and Jupyter. Ensure you have Anaconda or Miniconda installed before running these commands.

## Step 3: Select Your Runtime Environment

AI-For-Beginners supports multiple execution environments depending on your hardware and preferences:

**Local Jupyter (Recommended for most users):**

```bash
jupyter notebook

# Or for the newer interface:

jupyter lab

```

**Visual Studio Code:**
Open the cloned folder in VS Code. When prompted, install the Python and Jupyter extensions to run notebooks directly inside the editor without launching a separate browser.

**GitHub Codespaces:**
Click **Code → Codespaces → New codespace** on the GitHub repository page. This provisions a cloud VM with the Conda environment pre-configured, requiring zero local setup.

**Binder:**
Click the Binder badge in the main [`README.md`](https://github.com/microsoft/AI-For-Beginners/blob/main/README.md) to launch a free, web-based Jupyter server. Note that some network-restricted datasets may fail to load in this environment.

**GPU-Enabled Cloud:**
For compute-intensive lessons involving deep learning training, spin up an Azure Data Science VM or Azure Machine Learning notebook, then `git clone` the repository inside the VM to access GPU acceleration.

## Step 4: Run Beginner Examples

Before starting the full curriculum, test your setup with the self-contained scripts in `examples/`. According to [`examples/README.md`](https://github.com/microsoft/AI-For-Beginners/blob/main/examples/README.md), these provide immediate feedback:

```bash

# Pattern recognition demo

python examples/01-hello-ai-world.py

# Neural network from scratch

python examples/02-simple-neural-network.py

# Image classifier notebook

jupyter notebook examples/03-image-classifier.ipynb

```

These scripts verify that TensorFlow, PyTorch, and OpenCV are properly installed in your `ai4beg` environment.

## Step 5: Start the Curriculum

Begin with the course setup lessons located in `lessons/0-course-setup/`:

1. Read [`lessons/0-course-setup/setup.md`](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/0-course-setup/setup.md) for repository layout and self-study workflow instructions.
2. Follow [`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) for detailed execution commands.
3. Proceed to [`lessons/1-Intro/README.md`](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/1-Intro/README.md) to start the formal 12-week curriculum.

Each lesson follows a consistent structure: a pre-lecture quiz (via the quiz app), theoretical content in the README, practical Jupyter notebooks (available in both PyTorch and TensorFlow variants), hands-on labs, and a post-lecture quiz.

## Step 6: Launch the Quiz Application (Optional)

To run the integrated Vue 2 quiz app locally for offline access to quizzes:

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

```

This serves the application at `http://localhost:8080`, allowing you to take quizzes without internet connectivity after the initial setup.

## Summary

- **AI-For-Beginners** is a 12-week curriculum stored in `lessons/` with supporting code in `examples/`.
- Use `conda env create --name ai4beg --file .devcontainer/environment.yml` to install all required dependencies including TensorFlow and PyTorch.
- Choose between local Jupyter, VS Code, GitHub Codespaces, or Binder based on your hardware constraints.
- Start with [`lessons/0-course-setup/setup.md`](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/0-course-setup/setup.md) before progressing to lesson 1.
- Run [`examples/01-hello-ai-world.py`](https://github.com/microsoft/AI-For-Beginners/blob/main/examples/01-hello-ai-world.py) to verify your environment configuration.
- Access quizzes through the Vue app in `etc/quiz-app/` or use the hosted version linked in the main README.

## Frequently Asked Questions

### Do I need a GPU to complete the AI-For-Beginners curriculum?

No, the majority of the 24 lessons are designed to run on CPU-only machines. However, later lessons involving convolutional neural networks and large-scale training will execute significantly faster with GPU acceleration. For these sections, use GitHub Codespaces with GPU support or an Azure Machine Learning notebook.

### Can I run the AI-For-Beginners notebooks without installing Python locally?

Yes, you can use **GitHub Codespaces** for a fully configured cloud environment, or click the **Binder** badge in the repository's [`README.md`](https://github.com/microsoft/AI-For-Beginners/blob/main/README.md) to launch a temporary Jupyter server in your browser. These options require no local installation but may have session time limits or dataset access restrictions.

### What is the difference between the PyTorch and TensorFlow notebooks?

Each lesson in the `lessons/` directory typically contains two versions of the same notebook: one implemented in **PyTorch** and one in **TensorFlow/Keras**. The underlying AI concepts remain identical, but the code syntax and API calls differ. You can complete the curriculum using either framework based on your preference or industry requirements.

### How do I access the lesson quizzes?

Quizzes are integrated into the Vue 2 application located in `etc/quiz-app/`. You can run it locally by executing `npm install` and `npm run serve` in that directory, or access the hosted version linked from the main repository page. Each lesson includes pre-lecture and post-lecture quizzes to reinforce learning.