• 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.

• Consider authentication for Cognitive Services
• Manage network security for Cognitive Services

• Monitor Cognitive Services costs
• Create alerts
• View metrics
• Manage diagnostic logging

• Create Containers for Reuse
• Deploy to a Container
• Secure a Container
• Consume Cognitive Services from a Container

• Detect language
• Extract key phrases
• Analyze sentiment
• Extract entities
• Extract linked entities

• Provision a Translator resource
• Understand language detection, translation, and transliteration
• Specify translation options
• Define custom translations

• 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)

• Provision Azure resources for speech translation.
• Generate text translation from speech.
• Synthesize spoken translations.

• 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

• Understand capabilities of a Language Understanding app
• Process predictions from a Language Understanding app
• Deploy a language understanding app in a container

• 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

• Understand principles of bot design
• Use the Bot Framework SDK to build a bot
• Deploy a bot to Azure

• Understand dialogs
• Plan conversational flow
• Design the user experience
• Create a bot with the Bot Framework Composer

• Provision a Computer Vision resource
• Analyze an image
• Generate a smart-cropped thumbnail

• Describe Video Analyzer for Media capabilities
• Extract custom insights
• Use Video Analyzer for Media widgets and APIs

• Provision Azure resources for Custom Vision
• Understand image classification
• Train an image classifier

• Provision Azure resources for Custom Vision
• Understand object detection
• Train an object detector
• Consider options for labeling images

• 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

• 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

• 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

• Create an Azure Cognitive Search solution
• Develop a search application

• Implement a custom skill for Azure Cognitive Search
• Integrate a custom skill into an Azure Cognitive Search skillset

• Create a knowledge store from an Azure Cognitive Search pipeline
• View data in projections in a knowledge store

A: This AI102 training is suitable for professionals who are involved in designing and implementing AI solutions using Microsoft Azure. It is ideal for AI solution architects, developers, data scientists, and AI enthusiasts who want to leverage the power of Azure’s AI capabilities.

A: The training covers a wide range of topics, including designing AI solutions using Azure Cognitive Services, implementing computer vision solutions, developing natural language processing applications, building conversational AI solutions with Azure Bot Service, implementing speech recognition, and leveraging Azure Cognitive Search.

A: By completing this training, you will acquire comprehensive skills in designing and implementing AI solutions using Microsoft Azure. You will learn how to leverage Azure Cognitive Services for various AI tasks, implement computer vision solutions to analyze and process images, develop applications with natural language processing capabilities, create conversational AI solutions using Azure Bot Service, implement speech recognition functionalities, and utilize Azure Cognitive Search for advanced search capabilities.

A: Yes, there are prerequisites for the AI-102 training. Participants are expected to have a strong understanding of Azure services, experience with data science concepts, knowledge of Python programming, and familiarity with machine learning algorithms and frameworks.

A: Yes, participants will receive comprehensive course materials, including lecture slides, hands-on lab exercises, and reference materials to support their learning throughout the training.

A: Yes, upon successful completion of the AI-102 training, participants can choose to take the Microsoft certification exam AI-102: Designing and Implementing an Azure AI Solution to earn the Microsoft Certified: Azure AI Engineer Associate certification.

A: To enroll in the AI-102: Designing and Implementing a Microsoft Azure AI Solution training, click Enroll Now button or contact our training department for more information and registration details.

A: This training will provide you with the necessary skills and knowledge to design and implement AI solutions using Microsoft Azure, which is a highly sought-after skill in today’s technology-driven world. By gaining expertise in Azure AI, you can open doors to various job roles such as AI solution architect, AI developer, data scientist, and more. Additionally, earning the Microsoft Certified: Azure AI Engineer Associate certification can further enhance your career prospects and demonstrate your proficiency in Azure AI technologies.

A: While this training specifically focuses on designing and implementing AI solutions using Microsoft Azure, many of the concepts and principles can be applied to other cloud platforms as well. However, there may be differences in the specific services and implementations among different platforms.

A: This training will empower your organization to harness the power of AI and leverage Microsoft Azure’s AI capabilities. By designing and implementing AI solutions, your organization can automate processes, gain insights from data, improve customer experiences, and drive innovation. It enables you to stay competitive in the rapidly evolving digital landscape and unlock new opportunities for growth.