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Microsoft AI-102T00 - Designing and Implementing a Microsoft Azure AI Solution

  • Length 4 days
  • Price $3630 inc GST
  • Version A
Course overview
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Why study this course

This course 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.

Please note: Microsoft has retired Azure training from the Software Assurance Training Voucher (SATV) catalogue. From 1st February 2020 we are no longer able to accept SATVs for this course.

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What you’ll learn

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 analyse 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 analyse images and videos

  • Create custom computer vision models

  • Develop applications that detect, analyse, and recognise faces

  • Develop applications that read and process text in images and documents

  • Create intelligent search solutions for knowledge mining


Microsoft Azure at DDLS

DDLS is your best choice for training and certification in any of Microsoft’s leading technologies and services. We’ve been delivering effective training across all Microsoft products for over 30 years, and are proud to be Australia’s First and largest Microsoft Gold Learning Solutions Partner. All DDLS Microsoft courses follow Microsoft Official Curriculum (MOC) and are led by Microsoft Certified Trainers. Join more than 5,000 students who attend our quality Microsoft courses every year.


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Who is the course for?

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.

We can also deliver and customise this training course for larger groups – saving your organisation time, money and resources. For more information, please contact us on 1800 853 276.


Course subjects

Module 1: Introduction to AI on AzureArtificial 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.

Lessons

  • Introduction to Artificial Intelligence

  • Artificial Intelligence in Azure

Module 2: Developing AI Apps with Cognitive ServicesCognitive 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.

Lessons

  • Getting Started with Cognitive Services

  • Using Cognitive Services for Enterprise Applications

Lab : Get Started with Cognitive ServicesLab : Manage Cognitive Services SecurityLab : Monitor Cognitive ServicesLab : Use a Cognitive Services Container

Module 3: Getting Started with Natural Language ProcessingNatural 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 analyse and translate text.

Lessons

  • Analysing Text

  • Translating Text

Lab : Analyse TextLab : Translate Text

Module 4: Building Speech-Enabled ApplicationsMany modern apps and services accept spoken input and can respond by synthesising text. In this module, you’ll continue your exploration of natural language processing capabilities by learning how to build speech-enabled applications.

Lessons

  • Speech Recognition and Synthesis

  • Speech Translation

Lab : Recognise and Synthesise SpeechLab : Translate Speech

Module 5: Creating Language Understanding SolutionsTo 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.

Lessons

  • Creating a Language Understanding App

  • Publishing and Using a Language Understanding App

  • Using Language Understanding with Speech

Lab : Create a Language Understanding AppLab : Create a Language Understanding Client ApplicationLab : Use the Speech and Language Understanding Services

Module 6: Building a QnA SolutionOne 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.

Lessons

  • Creating a QnA Knowledge Base

  • Publishing and Using a QnA Knowledge Base

Lab : Create a QnA Solution

Module 7: Conversational AI and the Azure Bot ServiceBots 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.

Lessons

  • Bot Basics

  • Implementing a Conversational Bot

Lab : Create a Bot with the Bot Framework SDKLab : Create a Bot with Bot Framework Composer

Module 8: Getting Started with Computer VisionComputer 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 analyse images and video.

Lessons

  • Analysing Images

  • Analysing Videos

Lab : Analyze Images with Computer VisionLab : Analyse Video with Video Indexer

Module 9: Developing Custom Vision SolutionsWhile 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.

Lessons

  • Image Classification

  • Object Detection

Lab : Classify Images with Custom VisionLab : Detect Objects in Images with Custom Vision

Module 10: Detecting, Analysing, and Recognising FacesFacial detection, analysis, and recognition are common computer vision scenarios. In this module, you’ll explore the user of cognitive services to identify human faces.

Lessons

  • Detecting Faces with the Computer Vision Service

  • Using the Face Service

Lab : Detect, Analyse, and Recognise Faces

Module 11: Reading Text in Images and DocumentsOptical 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

  • Recogniser service

Lab : Read Text in ImagesLab : Extract Data from Forms

Module 12: Creating a Knowledge Mining SolutionUltimately, 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 analyse those insights.

Lessons

  • Implementing an Intelligent Search Solution

  • Developing Custom Skills for an Enrichment Pipeline

  • Creating a Knowledge Store

Lab : Create an Azure Cognitive Search solutionLab : Create a Custom Skill for Azure Cognitive SearchLab : Create a Knowledge Store with Azure Cognitive Search


Prerequisites

Before attending this course, students must have:

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

  • Knowledge of either C# or Python

  • Familiarity with JSON and REST programming semantics

To gain C# or Python skills, complete the free Take your first steps with C# or Take your first steps with Python learning path before attending the course.

If you are new to artificial intelligence, and want an overview of AI capabilities on Azure, consider completing the Azure AI Fundamentals training before taking this one.


Terms & Conditions

The supply of this course by DDLS is governed by the booking terms and conditions. Please read the terms and conditions carefully before enrolling in this course, as enrolment in the course is conditional on acceptance of these terms and conditions.



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