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.
Microsoft Azure AI Solution Training Delivery Methods
Microsoft Azure AI Solution Training Information
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
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
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.
Microsoft Azure AI Solution Training Outline
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.
- 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
Azure Cognitive Services enable developers to easily add AI capabilities into their applications. Learn how to create and consume these services.
- 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.
Securing Cognitive Services can help prevent data loss and privacy violations for user data that may be a part of the solution.
- Consider authentication for Cognitive Services
- Manage network security for 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.
- Monitor Cognitive Services costs
- Create alerts
- View metrics
- Manage diagnostic logging
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.
- Create Containers for Reuse
- Deploy to a Container
- Secure a Container
- Consume Cognitive Services from a Container
The Language service enables you to create intelligent apps and services that extract semantic information from text.
- Detect language
- Extract key phrases
- Analyze sentiment
- Extract entities
- Extract linked entities
The Translator service enables you to create intelligent apps and services that can translate text between languages.
- Provision a Translator resource
- Understand language detection, translation, and transliteration
- Specify translation options
- Define custom translations
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.
- 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)
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.
- Provision Azure resources for speech translation.
- Generate text translation from speech.
- Synthesize spoken translations.
The Language Understanding service enables you to train a language model that apps can use to extract meaning from natural language.
- 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
After creating a Language Understanding app, you can publish it and consume it from client applications.
- Understand capabilities of a Language Understanding app
- Process predictions from a Language Understanding app
- Deploy a language-understanding app in a container
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.
- 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
Learn how to build a bot by using the Microsoft Bot Framework SDK.
- Understand principles of bot design
- Use the Bot Framework SDK to build a bot
- Deploy a bot to Azure
User the Bot Framework Composer to quickly and easily build sophisticated conversational bots without writing code.
- Understand dialogs
- Plan conversational flow
- Design the user experience
- Create a bot with the Bot Framework Composer
With the Computer Vision service, you can use pre-trained models to analyze images and extract insights and information from them.
- Provision a Computer Vision resource
- Analyze an image
- Generate a smart-cropped thumbnail
Azure Video Analyzer for Media is a service to extract insights from video, including face identification, text recognition, object labels, scene segmentations, and more.
- Describe Video Analyzer for Media capabilities
- Extract custom insights
- Use Video Analyzer for Media widgets and APIs
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.
- Provision Azure resources for Custom Vision
- Understand image classification
- Train an image classifier
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.
- Provision Azure resources for Custom Vision
- Understand object detection
- Train an object detector
- Consider options for labeling images
The ability for applications to detect human faces, analyze facial features and emotions, and identify individuals is a key artificial intelligence capability.
- 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
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).
- 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
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.
- 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
Unlock the hidden insights in your data with Azure Cognitive Search.
- Create an Azure Cognitive Search solution
- Develop a search application
Use the power of artificial intelligence to enrich your data and find new insights.
- Implement a custom skill for Azure Cognitive Search
- Integrate a custom skill into an Azure Cognitive Search skillset
Persist the output from an Azure Cognitive Search enrichment pipeline for independent analysis or downstream processing.
- Create a knowledge store from an Azure Cognitive Search pipeline
- View data in projections in a knowledge store