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AI-102: Designing & Implementing a Microsoft Azure AI Solution Training

Category

Azure

Rating
4.5
(4.5)
Price

$2295

Course Description

Note: AI-102T00 is the replacement course for AI-100T00 .

Microsoft Azure AI Solution is a great course that is intended for all software developers. For any professional who wants to create an AI application, designing and implementing a Microsoft Azure AI solution is the course they need. This program describes the need for AI development in application.

After completing this program, professionals will create, configure, deploy, and secure the Azure cognizant services. As a developer, a professional will also create an application that analyzes a text. This certification program offers much more. It includes creating speech-enabled apps, development of applications with natural language understanding skills, creation of conversational bots, design of QNA, face recognition applications, and many more.

After successful completion of the course, professionals will establish themself as AI engineers.

This training is designed based on the objectives of the course variant AI-102T00-A.

Prerequisites for this training

Required

Who should attend this course?

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.

Schedules


Oct 04, 2021
9:00 am - 5:30 pm EST
Online

Oct 11, 2021
9:00 am - 5:30 pm EST
Online

Oct 18, 2021
9:00 am - 5:30 pm EST
Online

Oct 25, 2021
9:00 am - 5:30 pm EST
Online
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What you will learn

  • 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

With Microtek Learning, you’ll receive:

  • Certified Instructor-led training
  • Industry Best Trainers
  • Official Training Course Student Handbook
  • Pre and Post assessments/evaluations
  • Collaboration with classmates (not available for a self-paced course)
  • Real-world knowledge activities and scenarios
  • Exam scheduling support*
  • Learn and earn program*
  • Practice Tests
  • Knowledge acquisition and exam-oriented
  • Interactive online course.
  • Support from an approved expert
  • For Government and Private pricing*
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For many years, Microtek Learning has been helping organizations, leaders, and professionals to reach their maximum performance by addressing the challenges they are facing.

  • 300+ enterprise clients
  • 100,000+ professionals trained
  • Service 70 of the Fortune 100
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Curriculum

Artificial Intelligence (AI) is increasingly at the core of modern apps and services. In this module, you'll learn about some common AI capabilities that you can leverage in your apps, and how those capabilities are implemented in Microsoft Azure. You'll also learn about some considerations for designing and implementing AI solutions responsibly.

  • Introduction to Artificial Intelligence
  • Artificial Intelligence in Azure
  • After completing this module, students will be able to:

  • Describe considerations for creating AI-enabled applications
  • Identify Azure services for AI application development
  • Cognitive Services are the core building blocks for integrating AI capabilities into your apps. In this module, you'll learn how to provision, secure, monitor, and deploy cognitive services.

  • 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, students will be able to:

  • Provision and consume cognitive services in Azure
  • Manage cognitive services security
  • Monitor cognitive services
  • Use a cognitive services container
  • 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.

  • Analyzing Text
  • Translating Text
  • Lab: Analyze Text

    Lab: Translate Text

    After completing this module, students will be able to:

  • Use the Text Analytics cognitive service to analyze text
  • Use the Translator cognitive service to translate text
  • Many modern apps and services accept spoken input and can respond by synthesizing text. In this module, you'll continue your exploration of natural language processing capabilities by learning how to build speech-enabled applications.

  • Speech Recognition and Synthesis
  • Speech Translation
  • Lab: Recognize and Synthesize Speech

    Lab: Translate Speech

    After completing this module, students will be able to:

  • Use the Speech cognitive service to recognize and synthesize speech
  • Use the Speech cognitive service to translate speech
  • 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'll learn how to use the Language Understanding service to create an app that can identify user intent from natural language input.

  • Creating a Language Understanding App
  • Publishing and Using a Language Understanding App
  • Using Language Understanding with Speech
  • 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
  • One of the most common kinds of interaction between users and AI software agents is for users to submit questions in natural language, and for the AI agent to respond intelligently with an appropriate answer. In this module, you'll explore how the QnA Maker service enables the development of this kind of solution.

  • 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
  • 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'll explore the Microsoft Bot Framework and the Azure Bot Service, which together provide a platform for creating and delivering conversational experiences.

  • Bot Basics
  • Implementing a Conversational Bot
  • Lab: Create a Bot with the Bot Framework SDK

    Lab: Create a Bot with Bot Framework Composer

    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
  • Computer vision is an area of artificial intelligence in which software applications interpret visual input from images or video. In this module, you'll start your exploration of computer vision by learning how to use cognitive services to analyze images and video.

  • Analyzing Images
  • Analyzing Videos
  • 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
  • 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'll explore the Custom Vision service, and how to use it to create custom image classification and object detection, models.

  • 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 object detection
  • Facial detection, analysis, and recognition are common computer vision scenarios. In this module, you'll explore the user of cognitive services to identify human faces.

  • Detecting Faces with the Computer Vision Service
  • Using the Face Service
  • Lab: Detect, Analyze, and Recognize Faces

    After completing this module, students will be able to:

  • Detect faces with the Computer Vision service
  • Detect, analyze, and recognize faces with the Face service
  • 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 the text in images, documents, and forms.

  • 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
  • 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.

  • Implementing an Intelligent Search Solution
  • Developing Custom Skills for an Enrichment Pipeline
  • 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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    Course Details

    • Start Date: Oct 04, 2021
    • Duration: 4 Days
    • Skill Level: Intermediate
    • Certification: Yes
    • Enrolled: 1642
    • Price: $2295
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