# LearnAI-Airlift **Repository Path**: mirrors_Azure/LearnAI-Airlift ## Basic Information - **Project Name**: LearnAI-Airlift - **Description**: No description available - **Primary Language**: Unknown - **License**: CC-BY-4.0 - **Default Branch**: master - **Homepage**: None - **GVP Project**: No ## Statistics - **Stars**: 0 - **Forks**: 0 - **Created**: 2020-08-08 - **Last Updated**: 2026-04-04 ## Categories & Tags **Categories**: Uncategorized **Tags**: None ## README # LearnAI Team - Apps & Agents / Knowledge Mining Airlift ![Header](./slides/header.png) ## IMPORTANT MESSAGE - CONTENT RETIREMENT NOTICE The LearnAI team appreciates your visit, but this training was retired in 2019 and no further maintenance will be done. The team no longer exists and there is no creation of new content. You can use this material as is, no issues or PRs will be considered. To learn more about AI and Knowledge Mining, check this resources: + Microsoft AI School - http://aka.ms/ai-school + Azure Cognigite Search - Knowledge Mining Solution Accelerator - http://aka.ms/kmsolutions + Azure Cognigite Search - Knowledge Mining Workshop - http://aka.ms/kmw1 + Microsoft AI Customer Engineering Team Blog - http://aka.ms/ACE-Blog Thank you for the visit! ## About this course In this course, you will focus on hands-on activities that develop proficiency in AI-oriented services such as Azure Bot Services, Azure Search (including Cognitive Search), and Cognitive Services. Additionally, we will provide various design and architecture guidance/activities so you are not only able to build POC/solutions, but so you are also able to architect and design them. ## Goals Most challenges observed by customers in these realms are in stitching multiple services together. As such, where possible, we have tried to place key concepts in the context of broader examples. In this 300-400 level training you will: - Understand Microsoft Applied AI platform, including Cognitive Services, Bots, Azure Search, and Cognitive Search - Create an E2E Intelligent Search solution, using computer vision, Bing Search, LUIS (Language Understanding) and a Bot interface - Create an E2E Cognitive Search solution, using multiple Cognitive Services, Azure Functions and a Bot interface ## Agenda All labs have an approximate duration of 1 hour and start with an introduction of theory and context. ### Day 1 - Setup, Opening - [Cognitive Services Overview](https://azure.microsoft.com/en-us/services/cognitive-services/directory/) - [Intelligent Search Solution Architecture](https://github.com/Azure/LearnAI-Bootcamp/blob/master/lab01.1-computer_vision/0_README.md) - [Lab 1: Computer Vision](https://github.com/Azure/LearnAI-Bootcamp/blob/master/lab01.1-computer_vision/2_ImageProcessor.md) - [Lab 2: Custom Vision I: Image Classification](https://github.com/Azure/LearnAI-Bootcamp/blob/master/lab01.2_customvision01/0_README.md) - [Lab 3: Custom Vision II: Object Detection](https://github.com/Azure/LearnAI-Bootcamp/blob/master/lab01.3_customvision02/0_README.md) - [Lab 4: Azure Search](https://github.com/Azure/LearnAI-Bootcamp/blob/master/lab02.1-azure_search/0_README.md) - [Lab 5: LUIS](https://github.com/Azure/LearnAI-Bootcamp/blob/master/lab01.5-luis/0_README.md) - LearnAI Office Hours ### Day 2 - [Bot Architectures](https://github.com/Azure/LearnAI-DesigningandArchitectingIntelligentAgents/blob/master/04-architectures/1_session.md) - [Lab 6: Building Intelligent Bot](https://github.com/Azure/LearnAI-Bootcamp/blob/master/lab02.2-building_bots/0_README.md) - [Lab 7: Bing Search](https://github.com/Azure/LearnAI-Bootcamp/blob/master/lab02.3-bing_search/0_README.md) - [Cognitive Search Introduction](https://github.com/Azure/LearnAI-KnowledgeMiningBootcamp/blob/master/resources/md-files/introduction.md) - [Cognitive Search Solution Architecture](https://github.com/Azure/LearnAI-KnowledgeMiningBootcamp/blob/master/resources/md-files/solution-architecture.md) - [Cognitive Search Environment Creation](https://github.com/Azure/LearnAI-KnowledgeMiningBootcamp/blob/master/labs/lab-environment-creation.md) - LearnAI Office Hours ### Day 3 - [Lab 8: Azure Search](https://github.com/Azure/LearnAI-KnowledgeMiningBootcamp/blob/master/labs/lab-azure-search.md) - [Lab 9: Cognitive Search - Text Skills](https://github.com/Azure/LearnAI-KnowledgeMiningBootcamp/blob/master/labs/lab-text-skills.md) - [Lab 10: Cognitive Search - Image Skills](https://github.com/Azure/LearnAI-KnowledgeMiningBootcamp/blob/master/labs/lab-image-skills.md) - [Lab 11: Cognitive Search - Custom Skills](https://github.com/Azure/LearnAI-KnowledgeMiningBootcamp/blob/master/labs/lab-custom-skills.md) - [Lab 12: Cogntive Search Bot](https://github.com/Azure/LearnAI-KnowledgeMiningBootcamp/blob/master/labs/lab-bot-business-documents.md) - [Final Case / Hackathon](https://github.com/Azure/LearnAI-KnowledgeMiningBootcamp/blob/master/labs/lab-final-case.md) - Airlift Discussion, Q&A, and Feedback ## Contact Contact us: LearnAI@microsoft.com and ## Certifications The LearnAI team had intense participation in the creation of the following new Microsoft certifications and its required tests: + [Azure Data Engineer​](https://www.microsoft.com/en-us/learning/azure-data-engineer.aspx) + DP-200: Implementing an Azure Data Solution + DP-201: Designing an Azure Data Solutions​ + [Azure AI Engineer​](https://www.microsoft.com/en-us/learning/azure-ai-engineer.aspx) + AI-100: Designing and Implementing an Azure AI Solution + [Azure Data Scientist](https://www.microsoft.com/en-us/learning/azure-data-scientist.aspx) + DP-100: Designing and Implementing a Data Science Solution on Azure​ ## Cognitive Services Compliance Click [here](https://azure.microsoft.com/en-us/support/legal/cognitive-services-compliance-and-privacy/) to learn how Microsoft Cognitive Services handle your data. ## Contributing This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit When you submit a pull request, a CLA-bot will automatically determine whether you need to provide a CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions provided by the bot. You will only need to do this once across all repos using our CLA. This project has adopted the [Microsoft Open Source Code of Conduct](https://opensource.microsoft.com/codeofconduct/). For more information see the [Code of Conduct FAQ](https://opensource.microsoft.com/codeofconduct/faq/) or contact [opencode@microsoft.com](mailto:opencode@microsoft.com) with any additional questions or comments.