Designing and Implementing an Azure AI Solution (AI-102)

Duration: 4 days

Teaching method: classroom live and virtual classroom

Objectives | Audience | Prerequisites | Topics | Schedule

An Azure AI engineer works with Data Engineers and Data Scientists to analyze requirements for AI cloud-based and hybrid AI solutions and implements solutions. They are aware of the various components that make up the Microsoft Azure AI portfolio and related open source frameworks and technologies. The engineer leverages their knowledge to recommend appropriate tools and technologies for a given solution. The engineer is aware of the available data storage options and uses their understanding of cost models, capacity, and best practices to architect and implement AI solutions.

OBJECTIVES

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

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#, Python, or JavaScript and have knowledge on using REST-based APIs to build computer vision, language analysis, knowledge mining, intelligent search, and conversational AI solutions on Azure.

PREREQUISITES

Microsoft Azure Fundamentals (AZ-900) or an equivalent of this course. Before attending this course, students must have:

• Knowledge of Microsoft Azure and ability to navigate the Azure portal
• Knowledge of either C#, Python, or JavaScript

TOPICS

• Module 1: Introducing Azure Cognitive Services
  • Overview of Azure Cognitive Services
  • Creating a Cognitive Service on the Azure Portal
  • Access and Test a Cognitive Service
• Module 2: Creating Bots
  • Introducing the Bot Service
  • Creating a Basic Chat Bot
  • Testing with the Bot Emulator
• Module 3: Enhancing Bots with QnA Maker
  • Introducing QnA Maker
  • Implement a Knowledge Base with QnA Maker
  • Integrate QnA with a Bot
• Module 4: Learn How to Create Language Understanding Functionality with LUIS
  • Introducing Language Understanding
  • Create a new LUIS Service
  • Build Language Understanding with Intents and Utterances
• Module 5: Enhancing Your Bots with LUIS
  • Overview of language understanding for AI applications
  • Integrate LUIS and Bot to create an AI-based solution
• Module 6: Integrate Cognitive Services with Bots and Agents
  • Understand Cognitive Services for Bot Interactions
  • Perform Sentiment Analysis for your Bot with Text Analytics
  • Detect Language in a Bot with the Language Cognitive Services
  • Integrate Computer Vision with Bots

SCHEDULE