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Artificial Intelligence for Beginners - A Curriculum

 Sketchnote by (@girlie_mac)
AI For Beginners - Sketchnote by @girlie_mac

Explore the world of Artificial Intelligence (AI) with our 12-week, 24-lesson curriculum! It includes practical lessons, quizzes, and labs. The curriculum is beginner-friendly and covers tools like TensorFlow and PyTorch, as well as ethics in AI

What you will learn

Mindmap of the Course

In this curriculum, you will learn:

  • Different approaches to Artificial Intelligence, including the "good old" symbolic approach with Knowledge Representation and reasoning (GOFAI).
  • Neural Networks and Deep Learning, which are at the core of modern AI. We will illustrate the concepts behind these important topics using code in two of the most popular frameworks - TensorFlow and PyTorch.
  • Neural Architectures for working with images and text. We will cover recent models but may be a bit lacking in the state-of-the-art.
  • Less popular AI approaches, such as Genetic Algorithms and Multi-Agent Systems.

What we will not cover in this curriculum:

Find all additional resources for this course in our Microsoft Learn collection

For a gentle introduction to AI in the Cloud topics you may consider taking the Get started with artificial intelligence on Azure Learning Path.

Content

Lesson Link PyTorch/Keras/TensorFlow Lab
0 Course Setup Setup Your Development Environment
I Introduction to AI
01 Introduction and History of AI - -
II Symbolic AI
02 Knowledge Representation and Expert Systems Expert Systems / Ontology /Concept Graph
III Introduction to Neural Networks
03 Perceptron Notebook Lab
04 Multi-Layered Perceptron and Creating our own Framework Notebook Lab
05 Intro to Frameworks (PyTorch/TensorFlow) and Overfitting PyTorch / Keras / TensorFlow Lab
IV Computer Vision PyTorch / TensorFlow Explore Computer Vision on Microsoft Azure
06 Intro to Computer Vision. OpenCV Notebook Lab
07 Convolutional Neural Networks & CNN Architectures PyTorch /TensorFlow Lab
08 Pre-trained Networks and Transfer Learning and Training Tricks PyTorch / TensorFlow Lab
09 Autoencoders and VAEs PyTorch / TensorFlow
10 Generative Adversarial Networks & Artistic Style Transfer PyTorch / TensorFlow
11 Object Detection TensorFlow Lab
12 Semantic Segmentation. U-Net PyTorch / TensorFlow
V Natural Language Processing PyTorch /TensorFlow Explore Natural Language Processing on Microsoft Azure
13 Text Representation. Bow/TF-IDF PyTorch / TensorFlow
14 Semantic word embeddings. Word2Vec and GloVe PyTorch / TensorFlow
15 Language Modeling. Training your own embeddings PyTorch / TensorFlow Lab
16 Recurrent Neural Networks PyTorch / TensorFlow
17 Generative Recurrent Networks PyTorch / TensorFlow Lab
18 Transformers. BERT. PyTorch /TensorFlow
19 Named Entity Recognition TensorFlow Lab
20 Large Language Models, Prompt Programming and Few-Shot Tasks PyTorch
VI Other AI Techniques
21 Genetic Algorithms Notebook
22 Deep Reinforcement Learning PyTorch /TensorFlow Lab
23 Multi-Agent Systems
VII AI Ethics
24 AI Ethics and Responsible AI Microsoft Learn: Responsible AI Principles
IX Extras
25 Multi-Modal Networks, CLIP and VQGAN Notebook

Each lesson contains

  • Pre-reading material
  • Executable Jupyter Notebooks, which are often specific to the framework (PyTorch or TensorFlow). The executable notebook also contains a lot of theoretical material, so to understand the topic you need to go through at least one version of the notebook (either PyTorch or TensorFlow).
  • Labs available for some topics, which give you an opportunity to try applying the material you have learned to a specific problem.
  • Some sections contain links to MS Learn modules that cover related topics.

Getting Started

Don't forget to star (🌟) this repo to find it easier later.

Meet other Learners

Join our official AI Discord server to meet and network with other learners taking this course and get support.

Help Wanted

Do you have suggestions or found spelling or code errors? Raise an issue or create a pull request.

Special Thanks

Other Curricula

Our team produces other curricula! Check out:

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