Duration: 4 Days
Level: Intermediate
Learning Mode: Live Online Instructor-Led Training
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. Machine Learning, and Knowledge Mining to architect and implement Microsoft AI solutions involving natural language processing, speech, computer vision, bots, and agents.
Audience Profile
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.
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Skill
- 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.
- Create intelligent search, and conversational AI solutions on Azure.
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Pre-requisites
Before attending this course, students must have:
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General knowledge of networking, computing, and cloud concepts
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Knowledge of Microsoft Azure and ability to navigate the Azure portal
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Knowledge of either C# or Python
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Familiarity with JSON and REST programming semantics
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Course Agenda |
Module 1: Introduction to AI on Azure
Artificial Intelligence (AI) is increasingly at the core of modern apps and services. In this module, you will learn about some common AI capabilities that you can leverage in your apps, and how those capabilities are implemented in Microsoft Azure. You will also learn about some considerations for designing and implementing AI solutions responsibly.
Lessons
- Introduction to Artificial Intelligence
- Artificial Intelligence in Azure
- Select a cloud deployment
After completing this module, students will be able to:
- Describe considerations for creating AI-enabled applications.
- Identify Azure services for AI application development.
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Module 2: Developing AI Apps with Cognitive Services
Cognitive Services are the core building blocks for integrating AI capabilities into your apps. In this module, you will learn how to provision, secure, monitor, and deploy cognitive services.
Lessons
- Getting Started with Cognitive Services
- Using Cognitive Services for Enterprise Applications
Lab: Get Started with Cognitive Services
Lab: Manage Cognitive Services Security
Lab: Monitor Cognitive Services
Lab: Use a Cognitive Services Container
After completing this module, you will be able to:
- Provision and consume cognitive services in Azure.
- Manage cognitive services security.
- Monitor cognitive services.
- Use a cognitive service container
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Module 3: Getting Started with Natural Language Processing
Natural Language processing (NLP) is a branch of artificial intelligence that deals with extracting insights from written or spoken language. In this module, you'll learn how to use cognitive services to analyze and translate text.
Lessons
- Analyzing Text
- Translating Text
Lab: Analyze Text Lab: Translate Text
After completing this module, you will be able to:
- Use the Text Analytics cognitive service to analyze text.
- Use the Translator cognitive service to translate text.
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Module 4: Building Speech-Enabled Applications
Many modern apps and services accept spoken input and can respond by synthesizing text. In this module, you will continue your exploration of natural language processing capabilities by learning how to build speech-enabled applications.
Lessons
- Speech Recognition and Synthesis
- Speech Translation
Lab: Recognize and Synthesize Speech Lab: Translate Speech
After completing this module, you will be able to:
- Use the Speech cognitive service to recognize and synthesize speech.
- Use the Speech cognitive service to translate speech.
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Module 5: Omnichannel
Creating Language Understanding Solutions. To build an application that can intelligently understand and respond to natural language input, you must define and train a model for language understanding. In this module, you will learn how to use the Language Understanding service to create an app that can identify user intent from natural language input.
Lessons
- Publishing and Using a Language Understanding App
- Using Language Understanding with Speech
- Describe the service life cycle in Microsoft 365
Lab: Create a Language Understanding App Lab: Create a Language Understanding Client Application Lab: Use the Speech and Language Understanding Services
After completing this module, students will be able to:
- Create a Language Understanding app
- Create a client application for Language Understanding.
- Integrate Language Understanding and Speech
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Module 6: Building a QnA Solution
Learn more about Microsoft 365 licensing, service, and support options.
Lessons
- Creating a QnA Knowledge Base
- Publishing and Using a QnA Knowledge Base
Lab: Create a QnA Solution
After completing this module, students will be able to:
- Use QnA Maker to create a knowledge base.
- Use a QnA knowledge base in an app or bot.
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Module 7: Conversational AI and the Azure Bot Service
Bots are the basis for an increasingly common kind of AI application in which users engage in conversations with AI agents, often as they would with a human agent. In this module, you will explore the Microsoft Bot Framework and the Azure Bot Service, which together provide a platform for creating and delivering conversational experiences.
Lessons
- Bot Basics
- Implementing a Conversational Bot
Lab: Create a Bot with the Bot Framework SDK
Lab: Create a Bot with Bot Framework Cposerom
After completing this module, students will be able to:
- Use the Bot Framework SDK to create a bot.
- Use the Bot Framework Composer to create a bot.
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Module 8: Getting Started with Computer Vision
Getting Started with Computer Vision
Lessons
- Getting Started with Computer Vision
- Getting Started with Computer Vision
Lab: Analyze Images with Computer Vision
Lab: Analyze Video with Video Indexer
After completing this module, students will be able to:
- Use the Computer Vision service to analyze images.
- Use Video Indexer to analyze videos.
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Module 9: Developing Custom Vision Solutions
While there are many scenarios where pre-defined general computer vision capabilities can be useful, sometimes you need to train a custom model with your own visual data. In this module, you will explore the Custom Vision service, and how to use it to create custom image classification and object detection models.
Lessons
- Image Classification
- Object Detection
Lab: Classify Images with Custom Vision
Lab: Detect Objects in Images with Custom Vision
After completing this module, students will be able to:
- Use the Custom Vision service to implement image classification.
- Use the Custom Vision service to implement image classification.
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Module 10: Detecting, Analyzing, and Recognizing Faces
Facial detection, analysis, and recognition are common computer vision scenarios. In this module, you will explore the user of cognitive services to identify human faces.
Lessons
- Detecting Faces with the Computer Vision Service
- Detecting Faces with the Computer Vision Service
Lab: Detect, Analyze, and Recognize Faces
After completing this module, students will be able to
- After completing this module, students will be able to:
- Detect, analyze, and recognize faces with the Face service.
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Module 11: Reading Text in Images and Documents
Optical character recognition (OCR) is another common computer vision scenario, in which software extracts text from images or documents. In this module, you'll explore cognitive services that can be used to detect and read text in images, documents, and forms.
Lessons
- Reading text with the Computer Vision Service
- Extracting Information from Forms with the Form Recognizer service
Lab: Read Text in Images
Lab: Extract Data from Forms
After completing this module, students will be able to:
- Use the Computer Vision service to read text in images and documents.
- Use the Form Recognizer service to extract data from digital forms.
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Module 12: Creating a Knowledge Mining Solution
In this module, you will learn how to use Dynamics 365 Connected Customer Service to take data and help execute actual business actions on the data. Ultimately, many AI scenarios involve intelligently searching for information based on user queries. AI-powered knowledge mining is an increasingly important way to build intelligent search solutions that use AI to extract insights from large repositories of digital data and enable users to find and analyze those insights.
Lessons
- Lesson 1: Getting started with Connected Customer Service
- Lesson 2: Registering devices
- Implementing an Intelligent Search Solution
- Implementing an Intelligent Search Solution
- Creating a Knowledge Store
Lab: Create an Azure Cognitive Search solution
Lab Create a Custom Skill for Azure Cognitive Search
Lab: Create a Knowledge Store with Azure Cognitive Search
After completing this module, students will be able to:
- Create an intelligent search solution with Azure Cognitive Search
- Implement a custom skill in an Azure Cognitive Search enrichment pipeline.
- Use Azure Cognitive Search to create a knowledge store.
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Here is the course outline:
Artificial Intelligence (AI) is increasingly at the core of modern apps and services. In this module, you will learn about some common AI capabilities that you can leverage in your apps, and how those capabilities are implemented in Microsoft Azure. You will also learn about some considerations for designing and implementing AI solutions responsibly.
|
Cognitive Services are the core building blocks for integrating AI capabilities into your apps. In this module, you will learn how to provision, secure, monitor, and deploy cognitive services.
|
Natural Language processing (NLP) is a branch of artificial intelligence that deals with extracting insights from written or spoken language. In this module, you'll learn how to use cognitive services to analyze and translate text.
|
Many modern apps and services accept spoken input and can respond by synthesizing text. In this module, you will continue your exploration of natural language processing capabilities by learning how to build speech-enabled applications.
|
Creating Language Understanding Solutions. To build an application that can intelligently understand and respond to natural language input, you must define and train a model for language understanding. In this module, you will learn how to use the Language Understanding service to create an app that can identify user intent from natural language input.
|
Learn more about Microsoft 365 licensing, service, and support options.
|
Bots are the basis for an increasingly common kind of AI application in which users engage in conversations with AI agents, often as they would with a human agent. In this module, you will explore the Microsoft Bot Framework and the Azure Bot Service, which together provide a platform for creating and delivering conversational experiences.
|
Getting Started with Computer Vision
|
While there are many scenarios where pre-defined general computer vision capabilities can be useful, sometimes you need to train a custom model with your own visual data. In this module, you will explore the Custom Vision service, and how to use it to create custom image classification and object detection models.
|
Facial detection, analysis, and recognition are common computer vision scenarios. In this module, you will explore the user of cognitive services to identify human faces.
|
Optical character recognition (OCR) is another common computer vision scenario, in which software extracts text from images or documents. In this module, you'll explore cognitive services that can be used to detect and read text in images, documents, and forms.
|
In this module, you will learn how to use Dynamics 365 Connected Customer Service to take data and help execute actual business actions on the data. Ultimately, many AI scenarios involve intelligently searching for information based on user queries. AI-powered knowledge mining is an increasingly important way to build intelligent search solutions that use AI to extract insights from large repositories of digital data and enable users to find and analyze those insights.
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