1. Prepare to develop AI solutions on Azure
As an aspiring Azure AI Engineer, you should understand core concepts and principles of AI development, and the capabilities of Azure services used in AI solutions.
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2. Create and consume Azure AI services
Azure AI services enable developers to easily add AI capabilities into their applications. Learn how to create and consume these services.
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3. Secure Azure AI services
Securing Azure AI services can help prevent data loss and privacy violations for user data that may be a part of the solution.
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4. Monitor Azure AI services
Azure AI services enable you to integrate artificial intelligence into your applications and services. It's important to be able to monitor Azure AI Services in order to track utilization, determine trends, and detect and troubleshoot issues.
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5. Deploy Azure AI services in containers
Learn about Container support in Azure AI services allowing the use of APIs available in Azure and enable flexibility in where to deploy and host the services with Docker containers.
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6. Analyze images
With the Azure AI Vision service, you can use pre-trained models to analyze images and extract insights and information from them.
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7. Classify images
Image classification is used to determine the main subject of an image. You can use the Azure AI Custom Vision services to train a model that classifies images based on your own categorizations.
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8. Detect, analyze, and recognize faces
The ability for applications to detect human faces, analyze facial features and emotions, and identify individuals is a key artificial intelligence capability.
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9. Read Text in images and documents with the Azure AI Vision Service
Azure's AI Vision service uses algorithms to process images and return information. This module teaches you how to use the Image Analysis API for optical character recognition (OCR).
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10. Analyze video
Azure Video Indexer is a service to extract insights from video, including face identification, text recognition, object labels, scene segmentations, and more.
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11. Analyze text with Azure AI Language
The Azure AI Language service enables you to create intelligent apps and services that extract semantic information from text.
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12. Build a question answering solution
The question answering capability of the Azure AI Language service makes it easy to build applications in which users ask questions using natural language and receive appropriate answers.
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13. Build a conversational language understanding model
The Azure AI Language conversational language understanding service (CLU) enables you to train a model that apps can use to extract meaning from natural language.
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14. Create a custom text classification solution
The Azure AI Language service enables processing of natural language to use in your own app. Learn how to build a custom text classification project.
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15. Custom named entity recognition
Build a custom entity recognition solution to extract entities from unstructured documents
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16. Translate text with Azure AI Translator service
The Translator service enables you to create intelligent apps and services that can translate text between languages.
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17. Create speech-enabled apps with Azure AI services
The Azure AI Speech service enables you to build speech-enabled applications. This module focuses on using the speech-to-text and text to speech APIs, which enable you to create apps that are capable of speech recognition and speech synthesis.
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18. Translate speech with the Azure AI Speech service
Translation of speech builds on speech recognition by recognizing and transcribing spoken input in a specified language, and returning translations of the transcription in one or more other languages.
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19. Create an Azure AI Search solution
Unlock the hidden insights in your data with Azure AI Search.
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20. Create a custom skill for Azure AI Search
Use the power of artificial intelligence to enrich your data and find new insights.
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21. Create a knowledge store with Azure AI Search
Persist the output from an Azure AI Search enrichment pipeline for independent analysis or downstream processing.
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22. Plan an Azure AI Document Intelligence solution
Learn how to use Azure AI Document Intelligence to build solutions that analyze forms and output data for storage or further processing.
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23. Use prebuilt Form Recognizer models
Learn what data you can analyze by choosing prebuilt Forms Analyzer models and how to deploy these models in a Form Analyzer solution.
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24. Extract data from forms with Azure Document Intelligence
Azure Document Intelligence uses machine learning technology to identify and extract key-value pairs and table data from form documents with accuracy, at scale. This module teaches you how to use the Azure Document Intelligence Azure AI service.
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25. Get started with Azure OpenAI Service
This module provides engineers with the skills to begin building an Azure OpenAI Service solution.
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26. Build natural language solutions with Azure OpenAI Service
This module provides engineers with the skills to begin building apps that integrate with the Azure OpenAI Service.
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27. Apply prompt engineering with Azure OpenAI Service
Prompt engineering in Azure OpenAI is a technique that involves designing prompts for natural language processing models. This process improves accuracy and relevancy in responses, optimizing the performance of the model.
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28. Generate code with Azure OpenAI Service
This module shows engineers how to use the Azure OpenAI Service to generate and improve code.
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29. Generate images with Azure OpenAI Service
The Azure OpenAI service includes the DALL-E model, which you can use to generate original images based on natural language prompts.
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30. Implement Retrieval Augmented Generation (RAG) with Azure OpenAI Service
Azure OpenAI on your data allows developers to implement RAG with supported AI chat models to reference specific sources of data to ground the response.
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31. Fundamentals of Responsible Generative AI
Generative AI enables amazing creative solutions, but must be implemented responsibly to minimize the risk of harmful content generation.
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