Microsoft AI-102T00 - Designing and Implementing a Microsoft Azure AI Solution
- Length 4 days
- Version A
- Register interest
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
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.
Expert instructors with real world experience and the latest vendor- approved in-depth course content.
Chosen and awarded by the world’s leading vendors as preferred training partner.
No matter your chosen technologies or platforms, we can help you stay one step ahead.
Who is the course for?
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 via email on firstname.lastname@example.org
Module 1: Introduction to AI on Azure 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
Module 2: Developing AI Apps with Cognitive Services 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 ServicesLab : Manage Cognitive Services SecurityLab : Monitor Cognitive ServicesLab : Use a Cognitive Services Container
Module 3: Getting Started with Natural Language Processing 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 analyse and translate text.
Lab : Analyse TextLab : Translate Text
Module 4: Building Speech-Enabled Applications Many 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.
Speech Recognition and Synthesis
Lab : Recognise and Synthesise SpeechLab : Translate Speech
Module 5: Creating Language Understanding Solutions 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 AppLab : Create a Language Understanding Client ApplicationLab : Use the Speech and Language Understanding Services
Module 6: Building a QnA Solution 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
Module 7: Conversational AI and the Azure Bot Service 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.
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 Vision 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 analyse images and video.
Lab : Analyse Images with Computer VisionLab : Analyse Video with Video Indexer
Module 9: Developing Custom Vision Solutions 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.
Lab : Classify Images with Custom VisionLab : Detect Objects in Images with Custom Vision
Module 10: Detecting, Analysing, and Recognising Faces 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, Analyse, and Recognise Faces
Module 11: Reading Text in Images and Documents 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 text in images, documents, and forms.
Reading text with the Computer Vision Service
Extracting Information from Forms with the Form
Lab : Read Text in ImagesLab : Extract Data from Forms
Module 12: Creating a Knowledge Mining Solution 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 analyse those insights.
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
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
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.