AI-102T00 : Designing and Implementing a Microsoft Azure AI Solution (NEW course)

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AI-102T00 : Designing and Implementing a Microsoft Azure AI Solution (NEW 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# or Python as the programming language.

 

The duration of the program :

Classroom
Instructor Led : 32 h

Live Online
Instructor Led  : 32 h

Audience profile

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.

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.

Lessons

  • 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.

Lessons

  • Getting Started with Cognitive Services
  • Using Cognitive Services for Enterprise Applications

 

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 analyze and translate text.

Lessons

  • Analyzing Text
  • Translating Text

 

Module 4: Building Speech-Enabled Applications

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.

Lessons

  • Speech Recognition and Synthesis
  • Speech Translation

 

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.

Lessons

  • Creating a Language Understanding App
  • Publishing and Using a Language Understanding App
  • Using Language Understanding with Speech

 

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.

Lessons

  • Creating a QnA Knowledge Base
  • Publishing and Using a QnA Knowledge Base

 

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.

Lessons

  • Bot Basics
  • Implementing a Conversational Bot

 

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 analyze images and video.

Lessons

  • Analyzing Images
  • Analyzing Videos

 

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.

Lessons

  • Image Classification
  • Object Detection

 

Module 10: Detecting, Analyzing, and Recognizing 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.

Lessons

  • Detecting Faces with the Computer Vision Service
  • Using the Face Service

 

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.

Lessons

  • Reading text with the Computer Vision Service
  • Extracting Information from Forms with the Form Recognizer service

 

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 analyze those insights.

Lessons

  • Implementing an Intelligent Search Solution
  • Developing Custom Skills for an Enrichment Pipeline
  • Creating a Knowledge Store

Microsoft Certified: Azure AI Engineer Associate

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

Required Exam : AI-102

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 certification before taking this one.

Location Date Time (UTC +2 ) Delivery Format Language
Live Online*
14,15,16,17,18/6 Mon-Fri 17:00-22:15 Instructor Led Greek/English

* Σύγχρονη εξ αποστάσεως εκπαίδευση με εισηγητή – Virtual Class




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    Last update : 29/4/2021 (AI-102T00-A)