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

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

The AI-102T00: Designing and Implementing a Microsoft Azure AI Solution course is a comprehensive program designed to equip learners with the skills necessary to build, manage, and deploy AI solutions leveraging Microsoft Azure's powerful cloud-based services. The course covers a wide range of topics, from the fundamentals of AI and decision support solutions to more advanced areas like computer vision, natural language processing, and conversational AI.

Throughout the course, participants will engage with Cognitive Services, learning to select and implement the right services for various AI tasks such as vision, language, speech, and decision support solutions. The curriculum includes hands-on labs and exercises that allow learners to apply what they've learned in real-world scenarios, creating and deploying AI solutions on Azure.

By the end of the course, participants will have a solid understanding of how to create a Cognitive Services resource, manage security, and work with containers. They will also be able to analyze images and text, extract facial information, develop language understanding models, and build intelligent bots, all within the Azure AI ecosystem. This course is an excellent choice for those looking to enhance their skills in AI development and gain practical experience with Azure's AI capabilities.

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  • Live Online Training (Duration : 32 Hours)
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♱ Excluding VAT/GST

Classroom Training price is on request

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Course Prerequisites

To successfully undertake the training in the AI-102T00: Designing and Implementing a Microsoft Azure AI Solution course, students should possess the following minimum prerequisites:


  • Basic knowledge of Microsoft Azure services, particularly in the areas of compute, storage, and networking.
  • Fundamental understanding of the concepts of artificial intelligence and machine learning.
  • Experience with writing code in a high-level programming language such as Python, C#, or JavaScript.
  • Familiarity with RESTful services and APIs.
  • An understanding of JSON and data serialization/deserialization.
  • General knowledge of common data storage options (databases, blobs, etc.) and data formats (XML, JSON, etc.).
  • An inclination to learn about Azure Cognitive Services and building intelligent solutions on the Azure platform.

Note: While the above prerequisites are designed to ensure a smooth learning experience, our courses are structured to help all passionate learners get up to speed on AI with Azure, regardless of their initial skill level.


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

The AI-102T00 course focuses on implementing AI solutions using Microsoft Azure's services, tailored for IT professionals interested in AI application development.


  • Developers looking to specialize in AI-driven applications
  • Data Scientists seeking to operationalize AI models within Azure
  • Solution Architects designing AI solutions on Azure infrastructure
  • AI Engineers and Specialists aiming to expand their Azure AI skills
  • IT Professionals interested in integrating Azure AI services into existing business applications
  • Software Engineers who want to incorporate AI capabilities into their projects
  • Cloud Consultants advising on AI-powered cloud solutions
  • Technical Project Managers overseeing AI project implementations
  • DevOps Engineers managing AI application deployment and lifecycle
  • Technical Leads guiding teams on AI initiatives


Learning Objectives - What you will Learn in this AI-102T00: Designing and Implementing a Microsoft Azure AI Solution?

Introduction to Learning Outcomes

The AI-102T00 course equips students with skills to implement Microsoft Azure AI solutions, focusing on Cognitive Services, machine learning, and knowledge mining.

Learning Objectives and Outcomes

  • Understanding the fundamentals and applications of AI within the Azure ecosystem.
  • Selecting and deploying the appropriate Azure Cognitive Services for various AI tasks, including vision, language analysis, decision support, and speech solutions.
  • Developing and securing Azure AI solutions by implementing REST APIs, SDKs, and applying network security best practices.
  • Creating, configuring, and monitoring Cognitive Services resources while managing costs and implementing privacy policies.
  • Building natural language processing solutions with Azure AI Services for text analysis, translation, and creating conversational language understanding models.
  • Developing computer vision solutions to analyze images and videos, and implementing custom vision services for image classification and object detection.
  • Designing and deploying bots using Azure Bot Service, creating conversational AI experiences, and integrating with various Cognitive Services.
  • Implementing Azure Cognitive Search, Document Intelligence, and Azure OpenAI Service for intelligent search and data extraction from forms and documents.
  • Planning and implementing Cognitive Services in containers for edge and offline scenarios.
  • Managing a complete AI solution lifecycle, including versioning, monitoring, and continuous optimization and improvement.