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

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Big Data og AI
AI-102 Designing and Implementing a Microsoft Azure AI Solution kursus

Kursusmål

AI-102 Designing and Implementing an Azure AI Solution 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.

Deltagere

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.   

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 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

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

Kursusmateriale

Før kurset

Mulighed for at tale med en instruktør, der kan hjælpe dig med at finde det helt rigtige kursus.

På kurset

Undervisning af Danmarks mest erfarne instruktørteam i hyggelige og fuldt opdaterede kursuslokaler i centrum af København.
Et kursus bestående af en vekslen mellem teori og praktiske øvelser. Vi ved, hvor vigtigt det er, at du får tid til at arbejde med opgaverne i praksis, og derfor har vi altid fokus på hands-on i undervisningen.
Adgang til Microsofts digitale kursusmateriale (DMOC) samt Microsoft Labs Online.*
Fuld forplejning, som inkluderer morgenmad, friskbrygget kaffe, te, frugt, sodavand, frokost på en italiensk restaurant på Gråbrødretorv, kage, slik, og naturligvis Wi-Fi til dine devices.
Et kursuscertifikat med bevis på dine nye kvalifikationer.

Efter kurset

Adgang til vores gratis hotline, som betyder, at du op til et år efter kurset kan ringe eller skrive til os, hvis du har spørgsmål til de emner, der er blevet gennemgået på kurset.
Vores unikke tilfredshedsgaranti, som er din tryghed for at få fuldt udbytte af dit kursus.

Kurset bliver afholdt på dansk, men vi benytter Microsofts digitale materiale (DMOC), som er på engelsk. På kurset bliver der stillet en Surface tablet til rådighed, som kan anvendes til læsning af materialet. Du vil efterfølgende have adgang til materialet både online og lokalt. I tilfælde af at Microsoft laver en ny version af kursusmaterialet, vil du automatisk få adgang til det. Derudover vil du have adgang til øvelser via Microsoft Online Labs i 19 dage i alt, og du kan derfor fortsætte eller starte forfra på en øvelse hjemmefra, under eller efter kurset, alt efter behov.

Kursusindhold

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.

Lesson

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

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.

Lesson

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

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.

Lesson

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

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.

Lesson

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

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.

Lesson

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

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.

Lesson

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

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.

Lesson

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

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.

Lesson

Analyzing Images
Analyzing Videos

Lab : Analyze Images with Computer Vision

Lab : Analyze Video

After completing this module, students will be able to:

Use the Computer Vision service to analyze images
Use Video Analyzer to analyze 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.

Lesson

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

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.

Lesson

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

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.

Lesson

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

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.

Lesson

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: