AI-102T00: Designing and Implementing a Microsoft Azure AI Solution

Duration: 4 Days (32 Hours)

AI-102T00: Designing and Implementing a Microsoft Azure AI Solution Course Overview

The AI-102 Designing and Implementing an Azure AI Solution course is specifically designed for software developers who aim to create AI-powered applications using Azure Cognitive Services, Azure Cognitive Search, and Microsoft Bot Framework. This course offers comprehensive instruction and guidance on leveraging these Azure services to incorporate artificial intelligence capabilities into applications.
The course focuses on using either C# or Python as the programming language for development. Participants will gain practical knowledge and hands-on experience in utilizing Azure Cognitive Services to integrate natural language processing, computer vision, speech recognition, and other AI functionalities into their applications. They will also explore how to implement intelligent search capabilities using Azure Cognitive Search.
Furthermore, the course covers the Microsoft Bot Framework, enabling participants to design and develop intelligent chatbots and conversational agents. They will learn how to leverage Azure AI services to enhance the capabilities and effectiveness of these bots.
By the end of the AI-102 course, software developers will be equipped with the skills and expertise to design and implement AI solutions using Azure Cognitive Services, Azure Cognitive Search, and the Microsoft Bot Framework. They will have a solid understanding of how to incorporate AI functionalities into their applications, empowering them to create innovative and intelligent software solutions.

Audience Profile

The AI-102 Designing and Implementing an Azure AI Solution course is tailored for software engineers skilled in building, managing, and deploying AI solutions on Azure. With expertise in C# or Python and REST-based APIs, they can leverage Azure Cognitive Services, Azure Cognitive Search, and Microsoft Bot Framework. The course focuses on designing AI-infused applications, incorporating computer vision, language analysis, knowledge mining, intelligent search, and conversational AI. It enhances their capabilities in building and deploying sophisticated AI solutions on the Azure platform.

Job role: AI Engineer

Prepare to develop AI solutions on Azure
  • 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
  • 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

AI-102T00: Designing and Implementing a Microsoft Azure AI Solution Course Prerequisites:

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.

Q: What is the AI-102: Designing and Implementing a Microsoft Azure AI Solution training?

A: The AI-102 training is a comprehensive course designed to equip learners with the knowledge and skills to design and implement AI solutions using Microsoft Azure. This training focuses on various aspects of AI, including natural language processing, computer vision, speech recognition, and conversational AI.

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.

Discover the perfect fit for your learning journey

Choose Learning Modality

Live Online

  • Convenience
  • Cost-effective
  • Self-paced learning
  • Scalability

Classroom

  • Interaction and collaboration
  • Networking opportunities
  • Real-time feedback
  • Personal attention

Onsite

  • Familiar environment
  • Confidentiality
  • Team building
  • Immediate application

Training Exclusives

This course comes with following benefits:

  • Practice Labs.
  • Get Trained by Microsoft Certified Trainers (MCT).
  • Access to the recordings of your class sessions for 90 days.
  • Digital courseware
  • Experience 24*7 learner support.

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