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‎README.md

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# Artificial Intelligence for Beginners - A Curriculum
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> **This curriculum is being actively developed on GitHub. Look into [contributing](CONTRIBUTING.md) to see which areas require active contributions. Please consider this a pre-release, and do not actively use in the classroom yet!**
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> **This curriculum is being actively developed on GitHub. Look into [contributing](/etc/CONTRIBUTING.md) to see which areas require active contributions. Please consider this a pre-release, and do not actively use in the classroom yet!**
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Azure Cloud Advocates at Microsoft are pleased to offer a 12-week, 24-lesson curriculum all about **Artificial Intelligence**.
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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-57639-dmitryso) learning path on Microsoft Learn, or [AI Business School](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-57639-dmitryso), 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-57639-dmitryso)**. 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-57639-dmitryso), [natural language processing](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-57639-dmitryso) 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-57639-dmitryso) or [Azure Databricks](). 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-57639-dmitryso) and [Build and O perate Machine Learning Solutions with Azure Databricks](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-57639-dmitryso) learning paths.
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* Specific ML **Cloud Frameworks**, such as [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-57639-dmitryso) or [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-57639-dmitryso). 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-57639-dmitryso) 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-57639-dmitryso) 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-57639-dmitryso) 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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<tr><th>No</th><th>Lesson</th><th>Intro</th><th>PyTorch</th><th>Keras/TensorFlow</th><th>Lab</th></tr>
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<tr><td>I</td><td colspan="4"><b>Introduction to AI</b></td><td>PAT</td></tr>
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<tr><td>1</td><td>Introduction and History of AI</td><td><a href="1-Intro/README.md">Text</a></td><td></td><td></td><td></td></tr>
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<tr><td>1</td><td>Introduction and History of AI</td><td><a href="/lessons/1-Intro/README.md">Text</a></td><td></td><td></td><td></td></tr>
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<tr><td>II</td><td colspan="4"><b>Symbolic AI</b></td><td>PAT</td></tr>
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<tr><td>2 </td><td>Knowledge Representation and Expert Systems</td><td><a href="2-Symbolic/README.md">Text</a></td><td colspan="2"><a href="2-Symbolic/Animals.ipynb">Expert System</a>, <a href="2-Symbolic/FamilyOntology.ipynb">Ontology</a>, <a href="2-Symbolic/MSConceptGraph.ipynb">Concept Graph</a></td><td></td></tr>

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- Introduction
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- [Introduction to AI](../../../lessons/1-Intro/README.md)
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- [Knowledge Representation and Expert Systems](../../../lessons/2-Symbolic/README.md)
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- [Neural Networks - Perceptron](../../../lessons/3-NeuralNetworks/03-Perceptron/README.md)
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- [Neural Networks - Your Own Framework](../../../lessons/3-NeuralNetworks/04-OwnFramework/README.md)
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- [Neural Networks - Perceptron](../../../lessons/3-NeuralNetworks/05-Frameworks/README.md)
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- [Computer Vision - Convolutional Neural Networks](../../../lessons/4-ComputerVision/07-ConvNets/README.md)
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- [Computer Vision - Transfer Learning](../../../lessons/4-ComputerVision/08-TransferLearning/README.md)
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- [Computer Vision - Autoencoders](../../../lessons/4-ComputerVision/09-Autoencoders/README.md)
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- [Computer Vision - GANs](../../../lessons/4-ComputerVision/10-GANs/README.md)
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- [Computer Vision - Segmentation](../../../lessons/4-ComputerVision/12-Segmentation/README.md)
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- [NLP - Text Representation](../../../lessons/5-NLP/13-TextRep/README.md)
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- [NLP - Embeddings](../../../lessons/5-NLP/14-Embeddings/README.md)
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- [NLP - LanguageModeling](../../../lessons/5-NLP/15-LanguageModeling/README.md)
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- [NLP - RNNs](../../../lessons/5-NLP/16-RNN/README.md)
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- [NLP - Generative Networks](../../../lessons/5-NLP/17-GenerativeNetworks/README.md)
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- [NLP - Transformers](../../../lessons/5-NLP/18-Transformers/README.md)
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- [Other - Genetic Algorithms](../../../lessons/6-Other/21-GeneticAlgorithms/README.md)
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- [Other - Multiagent Systems](../../../lessons/6-Other/23-MultiagentSystems/README.md)
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- [Ethics](../../../lessons/7-Ethics/README.md)

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module.exports = {
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contents: ['docs/_sidebar.md'], // array of "table of contents" files path
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pathToPublic: 'pdf/readme.pdf', // path where pdf will stored
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contents: ['etc/docsify-to-pdf/docs/_sidebar.md'], // array of "table of contents" files path
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pathToPublic: 'etc/docsify-to-pdf/pdf/readme.pdf', // path where pdf will stored
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pdfOptions: {
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margin: { top: '100px', bottom: '100px' }
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}, // reference: https://github.com/GoogleChrome/puppeteer/blob/master/docs/api.md#pagepdfoptions

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