130 строки
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130 строки
20 KiB
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# Artificial Intelligence for Beginners - A Curriculum
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| ](./lessons/sketchnotes/ai-overview.png)|
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|:---:|
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| AI For Beginners - _Sketchnote by [@girlie_mac](https://twitter.com/girlie_mac)_ |
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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
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## What you will learn
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**[Mindmap of the Course](http://soshnikov.com/courses/ai-for-beginners/mindmap.html)**
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In this curriculum, you will learn:
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* Different approaches to Artificial Intelligence, including the "good old" symbolic approach with **Knowledge Representation** and reasoning ([GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence)).
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* **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](http://Tensorflow.org) and [PyTorch](http://pytorch.org).
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* **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.
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* Less popular AI approaches, such as **Genetic Algorithms** and **Multi-Agent Systems**.
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What we will not cover in this curriculum:
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> [Find all additional resources for this course in our Microsoft Learn collection](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)
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* Business cases of using **AI in Business**. Consider taking [Introduction to AI for business users](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) learning path on Microsoft Learn, or [AI Business School](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum), developed in cooperation with [INSEAD](https://www.insead.edu/).
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* **Classic Machine Learning**, which is well described in our [Machine Learning for Beginners Curriculum](http://github.com/Microsoft/ML-for-Beginners).
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* Practical AI applications built using **[Cognitive Services](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)**. For this, we recommend that you start with modules Microsoft Learn for [vision](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum), [natural language processing](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum), **[Generative AI with Azure OpenAI Service](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** and others.
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* Specific ML **Cloud Frameworks**, such as [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum), [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum), or [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum). Consider using [Build and operate machine learning solutions with Azure Machine Learning](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) and [Build and Operate Machine Learning Solutions with Azure Databricks](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum) learning paths.
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* **Conversational AI** and **Chat Bots**. There is a separate [Create conversational AI solutions](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum) learning path, and you can also refer to [this blog post](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) for more detail.
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* **Deep Mathematics** behind deep learning. For this, we would recommend [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618) by Ian Goodfellow, Yoshua Bengio and Aaron Courville, which is also available online at [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/).
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For a gentle introduction to _AI in the Cloud_ topics you may consider taking the [Get started with artificial intelligence on Azure](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum) Learning Path.
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# Content
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| | Lesson Link | PyTorch/Keras/TensorFlow | Lab |
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| :-: | :------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------: | ------------------------------------------------------------------------------ |
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| 0 | [Course Setup](./lessons/0-course-setup/setup.md) | [Setup Your Development Environment](./lessons/0-course-setup/how-to-run.md) | |
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| I | [**Introduction to AI**](./lessons/1-Intro/README.md) | | |
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| 01 | [Introduction and History of AI](./lessons/1-Intro/README.md) | - | - |
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| II | **Symbolic AI** |
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| 02 | [Knowledge Representation and Expert Systems](./lessons/2-Symbolic/README.md) | [Expert Systems](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/2-Symbolic/Animals.ipynb) / [Ontology](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/2-Symbolic/FamilyOntology.ipynb) /[Concept Graph](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/2-Symbolic/MSConceptGraph.ipynb) | |
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| III | [**Introduction to Neural Networks**](./lessons/3-NeuralNetworks/README.md) |||
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| 03 | [Perceptron](./lessons/3-NeuralNetworks/03-Perceptron/README.md) | [Notebook](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/3-NeuralNetworks/03-Perceptron/Perceptron.ipynb) | [Lab](./lessons/3-NeuralNetworks/03-Perceptron/lab/README.md) |
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| 04 | [Multi-Layered Perceptron and Creating our own Framework](./lessons/3-NeuralNetworks/04-OwnFramework/README.md) | [Notebook](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/3-NeuralNetworks/04-OwnFramework/OwnFramework.ipynb) | [Lab](./lessons/3-NeuralNetworks/04-OwnFramework/lab/README.md) |
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| 05 | [Intro to Frameworks (PyTorch/TensorFlow) and Overfitting](./lessons/3-NeuralNetworks/05-Frameworks/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/3-NeuralNetworks/05-Frameworks/IntroPyTorch.ipynb) / [Keras](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/3-NeuralNetworks/05-Frameworks/IntroKeras.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Lab](./lessons/3-NeuralNetworks/05-Frameworks/lab/README.md) |
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| IV | [**Computer Vision**](./lessons/4-ComputerVision/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-computer-vision-pytorch/?WT.mc_id=academic-77998-cacaste) / [TensorFlow](https://docs.microsoft.com/learn/modules/intro-computer-vision-TensorFlow/?WT.mc_id=academic-77998-cacaste)| [Explore Computer Vision on Microsoft Azure](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) |
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| 06 | [Intro to Computer Vision. OpenCV](./lessons/4-ComputerVision/06-IntroCV/README.md) | [Notebook](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/4-ComputerVision/06-IntroCV/OpenCV.ipynb) | [Lab](./lessons/4-ComputerVision/06-IntroCV/lab/README.md) |
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| 07 | [Convolutional Neural Networks](./lessons/4-ComputerVision/07-ConvNets/README.md) & [CNN Architectures](./lessons/4-ComputerVision/07-ConvNets/CNN_Architectures.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/4-ComputerVision/07-ConvNets/ConvNetsPyTorch.ipynb) /[TensorFlow](https://microsoft.github.io/AI-For-Beginners/lessons/4-ComputerVision/07-ConvNets/ConvNetsTF.ipynb) | [Lab](./lessons/4-ComputerVision/07-ConvNets/lab/README.md) |
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| 08 | [Pre-trained Networks and Transfer Learning](./lessons/4-ComputerVision/08-TransferLearning/README.md) and [Training Tricks](./lessons/4-ComputerVision/08-TransferLearning/TrainingTricks.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/4-ComputerVision/08-TransferLearning/TransferLearningPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Lab](./lessons/4-ComputerVision/08-TransferLearning/lab/README.md) |
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| 09 | [Autoencoders and VAEs](./lessons/4-ComputerVision/09-Autoencoders/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/4-ComputerVision/09-Autoencoders/AutoEncodersPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/4-ComputerVision/09-Autoencoders/AutoencodersTF.ipynb) | |
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| 10 | [Generative Adversarial Networks & Artistic Style Transfer](./lessons/4-ComputerVision/10-GANs/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/4-ComputerVision/10-GANs/GANPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/4-ComputerVision/10-GANs/GANTF.ipynb) | |
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| 11 | [Object Detection](./lessons/4-ComputerVision/11-ObjectDetection/README.md) | [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/4-ComputerVision/11-ObjectDetection/ObjectDetection.ipynb) | [Lab](./lessons/4-ComputerVision/11-ObjectDetection/lab/README.md) |
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| 12 | [Semantic Segmentation. U-Net](./lessons/4-ComputerVision/12-Segmentation/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationPytorch.ipynb) / [TensorFlow](hhttps://microsoft.github.io/AI-For-Beginners/lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationTF.ipynb) | |
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| V | [**Natural Language Processing**](./lessons/5-NLP/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-pytorch/?WT.mc_id=academic-77998-cacaste) /[TensorFlow](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-TensorFlow/?WT.mc_id=academic-77998-cacaste) | [Explore Natural Language Processing on Microsoft Azure](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)|
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| 13 | [Text Representation. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
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| 14 | [Semantic word embeddings. Word2Vec and GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
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| 15 | [Language Modeling. Training your own embeddings](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [Lab](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
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| 16 | [Recurrent Neural Networks](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
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| 17 | [Generative Recurrent Networks](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.md) / [TensorFlow](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.md) | [Lab](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
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| 18 | [Transformers. BERT.](./lessons/5-NLP/18-Transformers/READMEtransformers.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
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| 19 | [Named Entity Recognition](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/19-NER/NER-TF.ipynb) | [Lab](./lessons/5-NLP/19-NER/lab/README.md) |
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| 20 | [Large Language Models, Prompt Programming and Few-Shot Tasks](./lessons/5-NLP/20-LangModels/READMELargeLang.md) | [PyTorch](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
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| VI | **Other AI Techniques** || |
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| 21 | [Genetic Algorithms](./lessons/6-Other/21-GeneticAlgorithms/README.md) | [Notebook](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/6-Other/21-GeneticAlgorithms/Genetic.ipynb) | |
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| 22 | [Deep Reinforcement Learning](./lessons/6-Other/22-DeepRL/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/6-Other/22-DeepRL/CartPole-RL-PyTorch.ipynb) /[TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/6-Other/22-DeepRL/CartPole-RL-TF.ipynb) | [Lab](./lessons/6-Other/22-DeepRL/lab/README.md) |
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| 23 | [Multi-Agent Systems](./lessons/6-Other/23-MultiagentSystems/README.md) | | |
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| VII | **AI Ethics** | | |
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| 24 | [AI Ethics and Responsible AI](./lessons/7-Ethics/README.md) | [Microsoft Learn: Responsible AI Principles](https://docs.microsoft.com/learn/paths/responsible-ai-business-principles/?WT.mc_id=academic-77998-cacaste) | |
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| IX | **Extras** | | |
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| 25 | [Multi-Modal Networks, CLIP and VQGAN](./lessons/X-Extras/X1-MultiModal/README.md) | [Notebook](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/X-Extras/X1-MultiModal/Clip.ipynb) | |
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## Each lesson contains
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* Pre-reading material
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* 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).
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* **Labs** available for some topics, which give you an opportunity to try applying the material you have learned to a specific problem.
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* Some sections contain links to [**MS Learn**](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) modules that cover related topics.
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## Getting Started
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- We have created a [setup lesson](./lessons/0-course-setup/setup.md) to help you with setting up your development environment. - For Educators, we have created a [curricula setup lesson](./lessons/0-course-setup/for-teachers.md) for you too!
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- How to [Run the code in a VSCode or a Codepace](./lessons/0-course-setup/how-to-run.md)
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Don't forget to star (🌟) this repo to find it easier later.
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## Meet other Learners
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Join our [official AI Discord server](https://aka.ms/genai-discord?WT.mc_id=academic-105485-bethanycheum) to meet and network with other learners taking this course and get support.
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## Quizzes
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> **A note about quizzes**: All quizzes are contained in the Quiz-app folder in etc\quiz-app, They are linked from within the lessons the quiz app can be run locally or deployed to Azure; follow the instruction in the `quiz-app` folder. They are gradually being localized.
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## Help Wanted
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Do you have suggestions or found spelling or code errors? Raise an issue or create a pull request.
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## Special Thanks
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* **✍️ Primary Author:** [Dmitry Soshnikov](http://soshnikov.com), PhD
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* **🔥 Editor:** [Jen Looper](https://twitter.com/jenlooper), PhD
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* **🎨 Sketchnote illustrator:** [Tomomi Imura](https://twitter.com/girlie_mac)
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* **✅ Quiz Creator:** [Lateefah Bello](https://github.com/CinnamonXI), [MLSA](https://studentambassadors.microsoft.com/)
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* **🙏 Core Contributors:** [Evgenii Pishchik](https://github.com/Pe4enIks)
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## Other Curricula
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Our team produces other curricula! Check out:
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* [Data Science for Beginners](https://aka.ms/ds4beginners)
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* [**Version 2.0** Generative AI for Beginners](https://aka.ms/genai-beginners)
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* [**NEW** Cybersecurity for Beginners](https://github.com/microsoft/Security-101??WT.mc_id=academic-96948-sayoung)
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* [Web Dev for Beginners](https://aka.ms/webdev-beginners)
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* [IoT for Beginners](https://aka.ms/iot-beginners)
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* [Machine Learning for Beginners](https://aka.ms/ml4beginners)
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* [XR Development for Beginners](https://aka.ms/xr-dev-for-beginners)
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* [Mastering GitHub Copilot for AI Paired Programming](https://aka.ms/GitHubCopilotAI)
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