Announcing a New Free Curriculum: Artificial Intelligence for Beginners
Tags: beginners, codenewbie, python, ai
Published: 2022-05-26 14:19:38

---
title: Announcing a New Free Curriculum: Artificial Intelligence for Beginners
published: true
description: Learn the basics of AI with Education Cloud Advocates at Microsoft, including GOFAI ("good old-fashioned AI"), symbolic reasoning, knowledge representation, neural networks, neural frameworks with TensorFlow and PyTorch, computer vision, semantic segmentation, Natural Language Processing, deep Reinforcement Learning, Genetic Algorithms, Multi-Agent Systems and AI Ethics
tags: beginners, codenewbie, python, ai
cover_image: https://dev-to-uploads.s3.amazonaws.com/uploads/articles/u4e6quuqyuwdvxs1hdus.png
---

It is our very great pleasure to announce the release of a new, free, MIT-licensed open-source curriculum all about Artificial Intelligence: **[AI for Beginners](https://aka.ms/ml-beginners)**. Brought to you by a team of Azure Cloud Advocates and Microsoft Student Ambassadors led by Cloud Advocate and Professor Dmitry Soshnikov, we hope to empower all students to learn the basics of AI. This self-driven course offers a full semester of content: a free 12-week, 24-lesson curriculum, with many labs and supplemental material to dive deep into the exciting field of AI. 

> [AI for Beginners](https://aka.ms/ml-beginners) joins our family of curricula by Microsoft:
> - [Web Dev for Beginners](https://aka.ms/webdev-beginners)
> - [Machine Learning for Beginners](https://aka.ms/ml-beginners)
> - [IoT for Beginners](https://aka.ms/iot-beginners)
> - [Data Science for Beginners](https://aka.ms/datascience-beginners)

## About the Course

Despite the name "AI for Beginners", this course is not a lightweight introductory course that will give you a basic idea of what AI is or teach how to use Cognitive Services or pre-trained models. It is a full-fledged course on AI, similar to one you might take in a university. However, we tried to make it a bit more applied and less theoretical -- accessible to students without a strong mathematical background.

## For Students 

Students can use this curriculum to learn the basics of AI and Neural Networks. In addition to text-based lessons, there are executable Jupyter Notebooks with samples, as well as labs that you can do to deepen your knowledge. You can run notebooks either on your local computer or in the cloud. Join your peers on [GitHub Discussion Boards](https://github.com/microsoft/AI-For-Beginners/discussions) to learn together and watch for [more learning opportunities online](https://twitter.com/shwars).

## For Teachers 

Educators can re-use this material in class or incorporate some of the samples into their own courses. Let us know if you decide to teach with all or part of this courseware!

## Contribute! 

The course is open for contributions, in particular translations! Make your mark by [contributing your language to the repo](https://github.com/microsoft/AI-For-Beginners/blob/main/etc/TRANSLATIONS.md).

We are also open to PRs and Issue raising, following our Code of Conduct and templating systems. We hope the community will chip in with translations of the lessons, quizzes and assignments. Thank you for participating as we learn together.

## Let's Learn Together

![Sketchnote by Tomomi](https://dev-to-uploads.s3.amazonaws.com/uploads/articles/17ky2xz7xkemagpb9h7l.png)

> Sketchnote by [Tomomi Imura](https://twitter.com/girlie_mac)

Our curricula include:

- a pre-lesson warmup quiz
- a written lesson
- knowledge checks
- infographics, sketchnotes, and visuals
- a challenge
- an assignment or lab, often for both PyTorch and TensorFlow
- a post-lesson quiz
- opportunities to deepen your knowledge on Microsoft Learn

## Topics

In this course, you'll learn

- An overview of the AI landscape and different approaches to intelligence
- GOFAI ("good old-fashioned AI"), symbolic reasoning and knowledge representation
- Neural networks and Neural frameworks: TensorFlow and PyTorch
- Computer Vision: from simple convolution networks to object detection and semantic segmentation
- Natural Language Processing: from simple recurrent networks to modern transformer-based architectures
- Deep Reinforcement Learning
- Other AI techniques, such as Genetic Algorithms and Multi-Agent Systems
- AI Ethics

![mindmap of the course](https://dev-to-uploads.s3.amazonaws.com/uploads/articles/9d5uo91euamy8bh2fvi9.png)

> A Mindmap of the Course, image from the repo

## Meet the team!

{% youtube m2KrAk0cC1c %}

## **Without further ado, please meet [AI For Beginners: A Curriculum](https://aka.ms/ai-beginners)!**