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 Microsoft Azure AI Solution Training course will use C# or Python as the programming language.
Сертификации:
This course can help you prepare for the following Microsoft role-based certification exam — Exam AI-102: Designing and Implementing a Microsoft Azure AI Solution.
Предварительные требования:
If you are new to artificial intelligence, and want an overview of AI capabilities on Azure, consider completing Microsoft Azure AI Fundamentals Training (AI-900) before taking this one. You should already 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
Цель курса:
In this course, you will learn how to:
Understand AI Solution Requirements
Design AI Solutions
Build and Train AI Models
Deploy AI Models
Integrate AI Models into Applications
Monitor and Maintain AI Solutions
Work with Cognitive Services
Implement Natural Language Processing (NLP) Solutions
Build Conversational AI Solutions
Understand Responsible AI Practices
Security and Compliance in AI Solutions
Module 1: Prepare to develop AI solutions on Azure
As an aspiring Azure AI Engineer, you should understand core concepts and principles of AI development, and the capabilities of Azure services used in AI solutions.
Lessons
Define artificial intelligence
Understand AI-related terms
Understand considerations for AI Engineers
Understand considerations for responsible AI
Understand capabilities of Azure Machine Learning
Understand capabilities of Azure Cognitive Services
Understand capabilities of the Azure Bot Service
Understand capabilities of Azure Cognitive Search
Module 2: Create and consume Cognitive Services
Azure Cognitive Services enable developers to easily add AI capabilities into their applications. Learn how to create and consume these services.
Lessons
Provision Cognitive Services resources in an Azure subscription.
Identify endpoints, keys, and locations required to consume a Cognitive Services resource.
Use a REST API to consume a cognitive service.
Use an SDK to consume a cognitive service.
Module 3: Secure Cognitive Services
Securing Cognitive Services can help prevent data loss and privacy violations for user data that may be a part of the solution.
Lessons
Consider authentication for Cognitive Services
Manage network security for Cognitive Services
Module 4: Monitor Cognitive Services
Azure Cognitive Services enable you to integrate artificial intelligence into your applications and services. It's important to be able to monitor Cognitive Services in order to track utilization, determine trends, and detect and troubleshoot issues.
Lessons
Monitor Cognitive Services costs
Create alerts
View metrics
Manage diagnostic logging
Module 5: Deploy cognitive services in containers
Learn about Container support in Cognitive Services allowing the use of APIs available in Azure and enable flexibility in where to deploy and host the services with Docker containers.
Lessons
Create Containers for Reuse
Deploy to a Container
Secure a Container
Consume Cognitive Services from a Container
Module 6: Extract insights from text with the Language service
The Language service enables you to create intelligent apps and services that extract semantic information from text.
Lessons
Module 7: Translate text with the Translator service
The Translator service enables you to create intelligent apps and services that can translate text between languages.
Lessons
Provision a Translator resource
Understand language detection, translation, and transliteration
Specify translation options
Define custom translations
Module 8: Create speech-enabled apps with the Speech service
The Speech service enables you to build speech-enabled applications. This module focuses on using the speech-to-text and text-to-speech APIs, which enable you to create apps that are capable of speech recognition and speech synthesis.
Lessons
Provision an Azure resource for the Speech service
Use the Speech to text API to implement speech recognition
Use the Text to speech API to implement speech synthesis
Configure audio format and voices
Use Speech Synthesis Markup Language (SSML)
Module 9: Translate speech with the speech service
Translation of speech builds on speech recognition by recognizing and transcribing spoken input in a specified language, and returning translations of the transcription in one or more other languages.
Lessons
Provision Azure resources for speech translation.
Generate text translation from speech.
Synthesize spoken translations.
Module 10: Build a Language Understanding model
The Language Understanding service enables you to train a language model that apps can use to extract meaning from natural language.
Lessons
Provision Azure resources for Language Understanding
Define intents, utterances, and entities
Use patterns to differentiate similar utterances
Use pre-built entity components
Train, test, publish, and review a Language Understanding model
Module 11: Publish and use a Language Understanding app
After creating a Language Understanding app, you can publish it and consume it from client applications.
Lessons
Understand capabilities of a Language Understanding app
Process predictions from a Language Understanding app
Deploy a language-understanding app in a container
Module 12: Build a question answering solution
The question-answering capability of the Language service makes it easy to build applications in which users ask questions using natural language and receive appropriate answers.
Lessons
Understand question answering
Compare question answering to language understanding
Create a knowledge base
Implement multi-turn conversation
Test and publish a knowledge base
Consume a knowledge base
Implement active learning
Create a question-answering bot
Module 13: Create a bot with the Bot Framework SDK
Learn how to build a bot by using the Microsoft Bot Framework SDK.
Lessons
Understand principles of bot design
Use the Bot Framework SDK to build a bot
Deploy a bot to Azure
Module 14: Create a Bot with the Bot Framework Composer
User the Bot Framework Composer to quickly and easily build sophisticated conversational bots without writing code.
Lessons
Understand dialogs
Plan conversational flow
Design the user experience
Create a bot with the Bot Framework Composer
Module 15: Analyze images
With the Computer Vision service, you can use pre-trained models to analyze images and extract insights and information from them.
Lessons
Provision a Computer Vision resource
Analyze an image
Generate a smart-cropped thumbnail
Module 16: Analyze video
Azure Video Analyzer for Media is a service to extract insights from video, including face identification, text recognition, object labels, scene segmentations, and more.
Lessons
Describe Video Analyzer for Media capabilities
Extract custom insights
Use Video Analyzer for Media widgets and APIs
Module 17: Classify images
Image classification is used to determine the main subject of an image. You can use the Custom Vision services to train a model that classifies images based on your own categorizations.
Lessons
Provision Azure resources for Custom Vision
Understand image classification
Train an image classifier
Module 18: Detect objects in images
Object detection is used to locate and identify objects in images. You can use Custom Vision to train a model to detect specific classes of object in images.
Lessons
Provision Azure resources for Custom Vision
Understand object detection
Train an object detector
Consider options for labeling images
Module 19: Detect, analyze, and recognize faces
The ability for applications to detect human faces, analyze facial features and emotions, and identify individuals is a key artificial intelligence capability.
Lessons
Identify options for face detection, analysis, and identification
Understand considerations for face analysis
Detect faces with the Computer Vision service
Understand capabilities of the Face service
Compare and match detected faces
Implement facial recognition
Module 20: Read Text in Images and Documents with the Computer Vision Service
Azure's Computer Vision service uses algorithms to process images and return information. This module teaches you how to use the Read API for optical character recognition (OCR).
Lessons
Read text from images with the Read API
Use the Computer Vision service with SDKs and the REST API
Develop an application that can read printed and handwritten text
Module 21: Extract data from forms with Form Recognizer
Form Recognizer uses machine learning technology to identify and extract key-value pairs and table data from form documents with accuracy, at scale. This module teaches you how to use the Azure Form Recognizer cognitive service.
Lessons
Identify how Form Recognizer's layout service, prebuilt models, and custom service can automate processes
Use Form Recognizer's Optical Character Recognition (OCR) capabilities with SDKs, REST API, and Form Recognizer Studio
Develop and test custom models
Module 22: Create an Azure Cognitive Search Solution
Unlock the hidden insights in your data with Azure Cognitive Search.
Lessons
Create an Azure Cognitive Search solution
Develop a search application
Module 23: Create a custom skill for Azure Cognitive Search
Use the power of artificial intelligence to enrich your data and find new insights.
Lessons
Module 24: Create a knowledge store with Azure Cognitive Search
Persist the output from an Azure Cognitive Search enrichment pipeline for independent analysis or downstream processing.
Lessons
Create a knowledge store from an Azure Cognitive Search pipeline
View data in projections in a knowledge store
