AI - 102 : Designing and Implementing an Azure AI Solution

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#, Python, or JavaScript as the programming language.

Audience Profile:

This course is tailored for software engineers focused on building, managing, and deploying AI solutions that utilize Azure Cognitive Services, Azure Cognitive Search, and Microsoft Bot Framework. Attendees should be familiar with C# or Python and have experience using REST-based APIs to develop solutions in areas such as computer vision, language analysis, knowledge mining, intelligent search, and conversational AI on Azure.

At Course Completion:
After completing this course, students will be able to:

• 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

• Build conversational solutions with bots

• Utilize 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

• Build intelligent search solutions for knowledge mining

Prerequisites:

Before attending this course, students should have:

• Knowledge of Microsoft Azure and ability to navigate the Azure portal

• Proficiency in either C# or Python

• Familiarity with JSON and REST programming semantics

Course Outline:

Module 1: Introduction to AI on Azure
Learn about AI capabilities and their implementation in Microsoft Azure, with a focus on responsible AI solution design.
Lessons:

• Introduction to Artificial Intelligence

• Artificial Intelligence in Azure

Outcomes:

• Describe considerations for AI-enabled applications.

• Identify Azure services for AI development.

Module 2: Developing AI Apps with Cognitive Services
Explore the core building blocks for integrating AI, including provisioning, securing, monitoring, and deploying cognitive services.
Lessons:

• Getting Started with Cognitive Services

• Using Cognitive Services for Enterprise Applications

Lab:

• Get Started with Cognitive Services

• Manage Cognitive Services Security

• Monitor Cognitive Services

• Use a Cognitive Services Container

Outcomes:

• Provision and consume cognitive services in Azure.

• Manage cognitive services security and monitoring.

• Use a cognitive service container.

Module 3: Getting Started with Natural Language Processing
Understand how to use cognitive services for text analysis and translation.
Lessons:

• Analyzing Text

• Translating Text

Lab:

• Analyze Text

• Translate Text

Outcomes:

• Use the Text Analytics service for text analysis.

• Use the Translator service for text translation.

Module 4: Building Speech-Enabled Applications
Learn to build applications that handle spoken input and text synthesis using speech cognitive services.
Lessons:

• Speech Recognition and Synthesis

• Speech Translation

Lab:

• Recognize and Synthesize Speech

• Translate Speech

Outcomes:

• Use the Speech service for speech recognition, synthesis, and translation.

Module 5: Creating Language Understanding Solutions
Train models for understanding natural language input and integrate them into applications.
Lessons:

• Creating a Language Understanding App

• Publishing and Using a Language Understanding App

• Using Language Understanding with Speech

Lab:

• Create a Language Understanding App

• Create a Language Understanding Client Application

• Use the Speech and Language Understanding Services

Outcomes:

• Create and deploy Language Understanding apps.

• Integrate Language Understanding with Speech.

Module 6: Building a QnA Solution
Develop AI solutions that intelligently respond to user questions using the QnA Maker service.
Lessons:

• Creating a QnA Knowledge Base

• Publishing and Using a QnA Knowledge Base

Lab:

• Create a QnA Solution

Outcomes:

• Use QnA Maker to create and deploy knowledge bases.

Module 7: Conversational AI and the Azure Bot Service
Build conversational bots using the Microsoft Bot Framework and Azure Bot Service.
Lessons:

• Bot Basics

• Implementing a Conversational Bot

Lab:

• Create a Bot with the Bot Framework SDK

• Create a Bot with Bot Framework Composer

Outcomes:

• Use the Bot Framework SDK and Composer to create bots.

Module 8: Getting Started with Computer Vision
Explore how to use cognitive services to analyze images and videos.
Lessons:

• Analyzing Images

• Analyzing Videos

Lab:

• Analyze Images with Computer Vision

• Analyze Video with Video Indexer

Outcomes:

• Use the Computer Vision service for image analysis.

• Use Video Indexer for video analysis.

Module 9: Developing Custom Vision Solutions
Learn to create custom image classification and object detection models using the Custom Vision service.
Lessons:

• Image Classification

• Object Detection

Lab:

• Classify Images with Custom Vision

• Detect Objects in Images with Custom Vision

Outcomes:

• Implement image classification and object detection using Custom Vision.

Module 10: Detecting, Analyzing, and Recognizing Faces
Discover how to use cognitive services for facial detection, analysis, and recognition.
Lessons:

• Detecting Faces with the Computer Vision Service

• Using the Face Service

Lab:

• Detect, Analyze, and Recognize Faces

Outcomes:

• Use the Face service for facial detection and recognition.

Module 11: Reading Text in Images and Documents
Learn to extract text from images, documents, and forms using OCR and Form Recognizer services.
Lessons:

• Reading Text with the Computer Vision Service

• Extracting Information from Forms with the Form Recognizer Service

Lab:

• Read Text in Images

• Extract Data from Forms

Outcomes:

• Use OCR to read text in images and documents.

• Use Form Recognizer to extract data from forms.

Module 12: Creating a Knowledge Mining Solution
Build intelligent search solutions using Azure Cognitive Search and custom skills for knowledge mining.
Lessons:

• Implementing an Intelligent Search Solution

• Developing Custom Skills for an Enrichment Pipeline

• Creating a Knowledge Store

Lab:

• Create an Azure Cognitive Search Solution

• Create a Custom Skill for Azure Cognitive Search

• Create a Knowledge Store with Azure Cognitive Search

Outcomes:

• Develop intelligent search solutions and custom skills.

• Create a knowledge store using Azure Cognitive Search.