Designing and Implementing a Microsoft Azure AI Solution

Designing and Implementing a Microsoft Azure AI Solution (AI-102T00)

Course Length: 4 days
Delivery Methods: Multiple delivery options
Course Overview

AI-102 Designing and Implementing an Azure AI Solution is intended for software developers wanting to build AI infused applications that leverage Azure Cognitive Services, Azure Cognitive Search, and Microsoft Bot Framework. The course will use C# or Python as the programming language.

Software engineers concerned with building, managing and deploying AI solutions that leverage Azure Cognitive Services, Azure Cognitive Search, and Microsoft Bot Framework. They are familiar with C# or Python and have knowledge on using REST-based APIs to build computer vision, language analysis, knowledge mining, intelligent search, and conversational AI solutions on Azure.

Course Benefits
  • Describe considerations for AI-enabled application development.
  • Create, configure, deploy, and secure Azure Cognitive Services.
  • Develop applications that analyze text.
  • Develop speech-enabled applications.
  • Create applications with natural language understanding capabilities.
  • Create QnA applications.
  • Create conversational solutions with bots.
  • Use computer vision services to analyze images and videos.
  • Create custom computer vision models.
  • Develop applications that detect, analyze, and recognize faces.
  • Develop applications that read and process text in images and documents.
  • Create intelligent search solutions for knowledge mining.
Available Delivery Methods
Public Class
Public expert-led online training from the convenience of your home, office or anywhere with an internet connection. Guaranteed to run .
Private Class
Private classes are delivered for groups at your offices or a location of your choice.
Microsoft Certified Partner

Webucator is a Microsoft Certified Partner for Learning Solutions (CPLS). This class uses official Microsoft courseware and will be delivered by a Microsoft Certified Trainer (MCT).

Course Outline
  1. Prepare to develop AI solutions on Azure
    1. Define artificial intelligence
    2. Understand AI-related terms
    3. Understand considerations for AI Engineers
    4. Understand considerations for responsible AI
    5. Understand capabilities of Azure Machine Learning
    6. Understand capabilities of Azure AI Services
    7. Understand capabilities of the Azure OpenAI Service
    8. Understand capabilities of Azure Cognitive Search
  2. Create and consume Azure AI services
    1. Provision an Azure AI services resource
    2. Identify endpoints and keys
    3. Use a REST API
    4. Use an SDK
  3. Secure Azure AI services
    1. Consider authentication
    2. Implement network security
  4. Monitor Azure AI services
    1. Monitor cost
    2. Create alerts
    3. View metrics
    4. Manage diagnostic logging
  5. Deploy Azure AI services in containers
    1. Understand containers
    2. Use Azure AI services containers
  6. Analyze images
    1. Provision an Azure AI Vision resource
    2. Analyze an image
    3. Generate a smart-cropped thumbnail and remove background
  7. Classify images
    1. Provision Azure resources for Azure AI Custom Vision
    2. Understand image classification
    3. Train an image classifier
  8. Detect, analyze, and recognize faces
    1. Identify options for face detection analysis and identification
    2. Understand considerations for face analysis
    3. Detect faces with the Azure AI Vision service
    4. Understand capabilities of the face service
    5. Compare and match detected faces
    6. Implement facial recognition
  9. Read Text in images and documents with the Azure AI Vision Service
    1. Explore Azure AI Vision options for reading text
    2. Use the Read API
  10. Analyze video
    1. Understand Azure Video Indexer capabilities
    2. Extract custom insights
    3. Use Video Analyzer widgets and APIs
  11. Analyze text with Azure AI Language
    1. Provision an Azure AI Language resource
    2. Detect language
    3. Extract key phrases
    4. Analyze sentiment
    5. Extract entities
    6. Extract linked entities
  12. Build a question answering solution
    1. Understand question answering
    2. Compare question answering to Azure AI Language understanding
    3. Create a knowledge base
    4. Implement multi-turn conversation
    5. Test and publish a knowledge base
    6. Use a knowledge base
    7. Improve question answering performance
  13. Build a conversational language understanding model
    1. Understand prebuilt capabilities of the Azure AI Language service
    2. Understand resources for building a conversational language understanding model
    3. Define intents, utterances, and entities
    4. Use patterns to differentiate similar utterances
    5. Use pre-built entity components
    6. Train, test, publish, and review a conversational language understanding model
  14. Create a custom text classification solution
    1. Understand types of classification projects
    2. Understand how to build text classification projects
  15. Custom named entity recognition
    1. Understand custom named entity recognition
    2. Label your data
    3. Train and evaluate your model
  16. Translate text with Azure AI Translator service
    1. Provision an Azure AI Translator resource
    2. Specify translation options
    3. Define custom translations
  17. Create speech-enabled apps with Azure AI services
    1. Provision an Azure resource for speech
    2. Use the Azure AI Speech to Text API
    3. Use the text to speech API
    4. Configure audio format and voices
    5. Use Speech Synthesis Markup Language
  18. Translate speech with the Azure AI Speech service
    1. Provision an Azure resource for speech translation
    2. Translate speech to text
    3. Synthesize translations
  19. Create an Azure AI Search solution
    1. Manage capacity
    2. Understand search components
    3. Understand the indexing process
    4. Search an index
    5. Apply filtering and sorting
    6. Enhance the index
  20. Create a custom skill for Azure AI Search
    1. Create a custom skill
    2. Add a custom skill to a skillset
  21. Create a knowledge store with Azure AI Search
    1. Define projections
    2. Define a knowledge store
  22. Plan an Azure AI Document Intelligence solution
    1. Understand AI Document Intelligence
    2. Plan Azure AI Document Intelligence resources
    3. Choose a model type
  23. Use prebuilt Form Recognizer models
    1. Understand prebuilt models
    2. Use the General Document, Read, and Layout models
    3. Use financial, ID, and tax models
  24. Extract data from forms with Azure Document Intelligence
    1. What is Azure Document Intelligence?
    2. Get started with Azure Document Intelligence
    3. Train custom models
    4. Use Azure Document Intelligence models
    5. Use the Azure Document Intelligence Studio
  25. Get started with Azure OpenAI Service
    1. Access Azure OpenAI Service
    2. Use Azure OpenAI Studio
    3. Explore types of generative AI models
    4. Deploy generative AI models
    5. Use prompts to get completions from models
    6. Test models in Azure OpenAI Studio's playgrounds
  26. Build natural language solutions with Azure OpenAI Service
    1. Integrate Azure OpenAI into your app
    2. Use Azure OpenAI REST API
    3. Use Azure OpenAI SDK
  27. Apply prompt engineering with Azure OpenAI Service
    1. Understand prompt engineering
    2. Write more effective prompts
    3. Provide context to improve accuracy
  28. Generate code with Azure OpenAI Service
    1. Construct code from natural language
    2. Complete code and assist the development process
    3. Fix bugs and improve your code
  29. Generate images with Azure OpenAI Service
    1. What is DALL-E?
    2. Explore DALL-E in Azure OpenAI Studio
    3. Use the Azure OpenAI REST API to consume DALL-E models
  30. Implement Retrieval Augmented Generation (RAG) with Azure OpenAI Service
    1. Understand Retrieval Augmented Generation (RAG) with Azure OpenAI Service
    2. Add your own data source
    3. Chat with your model using your own data
  31. Fundamentals of Responsible Generative AI
    1. Plan a responsible generative AI solution
    2. Identify potential harms
    3. Measure potential harms
    4. Mitigate potential harms
    5. Operate a responsible generative AI solution
Class Materials

Each student will receive a comprehensive set of materials, including course notes and all the class examples.

Class Prerequisites

Experience in the following is required for this AI class:

  • Knowledge of Microsoft Azure and ability to navigate the Azure portal.
  • Knowledge of either C# or Python.
  • Familiarity with JSON and REST programming semantics.
Live Public Class
$2,445.10 / student
Please select a class.
Live Private Class
  • Private Class for your Team
  • Live training
  • Online or On-location
  • Customizable
  • Expert Instructors
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