Designing and Implementing an Azure AI Solution course AI-100

Azure AI Engineers use Cognitive Services, Machine Learning, and Knowledge Mining to architect and implement Microsoft AI solutions involving natural language processing, speech, computer vision, bots, and agents. Designing and Implementing an Azure AI Solution course AI-100

Exam AI-100: Designing and Implementing an Azure AI Solution

This exam measures your ability to accomplish the following technical tasks: analyze solution requirements; design solutions; integrate AI models into solutions; and deploy and manage solutions.

The following course prepare the exam AI-100:

Course AI-100: Designing and Implementing an Azure AI Solution

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.

This course teaches the concepts of Azure AI engineering by presenting, and developing, a scenario that creates a customer support Bot that utilizes various tools and services in the Azure AI landscape like language understanding, QnA Maker, and various Azure Cognitive Services to implement language detection, text analytics, and computer vision.

Course Outline

Module 1: Introducing Azure Cognitive Services

The student will learn about the available Cognitive Services on Microsoft Azure and their role in architecting AI solutions.

Lessons

Overview of Azure Cognitive Services

Creating a Cognitive Service on the Azure Portal

Access and Test a Cognitive Service

Module 2: Creating Bots

The student will learn about the Microsoft Bot Framework and Bot Services.

Lessons

Introducing the Bot Service

Creating a Basic Chat Bot

Testing with the Bot Emulator

Module 3: Enhancing Bots with QnA Maker

The student will learn about the QnA Maker and how to integrate Bots and QnA Maker to build up a useful knowledge base for user interactions.

Lessons

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

The student will learn about LUIS and how to create intents and utterances to support a natural language processing solution.

Lessons

Introducing Language Understanding

Create a new LUIS Service

Build Language Understanding with Intents and Utterances

Module 5: Enhancing Your Bots with LUIS

The student will learn about integrating LUIS with a Bot to better understand the users’ intentions when interacting with the Bot.

Lessons

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

The student will learn about integrating Bots and Agents with Azure Cognitive Services for advanced features such as sentiment analysis, image and text analysis, and OCR and object detection.

Lessons

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

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