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AI-102T00-A: Develop AI solutions in Azure

  • 4.8(11,826 Rating)

Course Overview

The Develop AI Solutions in Azure (AI-102) course is an advanced, role-based training programme designed for professionals who want to design, build, deploy, and manage AI-powered solutions using Microsoft Azure. This course focuses on translating artificial intelligence concepts into production-ready applications that are scalable, secure, and aligned with business objectives.

Participants will gain in-depth knowledge of Azure AI services, including Azure AI Foundry, Azure OpenAI, Cognitive Services, Azure Machine Learning, and search solutions. The course emphasises real-world implementation of AI workloads such as natural language processing, computer vision, conversational AI, document intelligence, and generative AI applications.

Beyond development, the course addresses solution architecture, integration, performance optimisation, security, monitoring, and responsible AI practices. Learners will work with modern DevOps-aligned workflows to improve transparency, collaboration, and lifecycle management of AI solutions in enterprise environments. This training is fully aligned with the Microsoft Azure AI Engineer Associate (AI-102) certification.

Develop AI Solutions in Azure – Training Outcomes:

This training equips professionals with the skills required to design, develop, and deploy production-ready AI solutions on Microsoft Azure. Upon successful completion of the course, participants will be able to:

  • Architect, build, and deploy AI-powered applications using Azure AI Foundry, following best practices for scalability, security, and performance.
  • Design and implement generative AI solutions leveraging large language models (LLMs) to extend application functionality and enhance user experiences.
  • Develop and manage AI agents to automate complex tasks, workflows, and decision-making processes in enterprise environments.
  • Implement natural language processing (NLP) solutions for real-world use cases such as text analysis, language understanding, and conversational interfaces.
  • Build and integrate computer vision capabilities to enable image analysis, object detection, and visual intelligence within applications.
  • Apply information extraction techniques to process, analyse, and structure unstructured data, enabling actionable insights and intelligent automation.

Training Prerequisites:

If you are new to artificial intelligence and want an overview of AI capabilities on Azure, consider completing Introduction to AI in Azure (AI-900) before taking this one. You should already have:

  • Knowledge of Microsoft Azure and the ability to navigate the Azure portal
  • Knowledge of either C# or Python
  • Familiarity with JSON and REST programming semantics

Certification Information

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.

Schedule Dates

13 April 2026 - 17 April 2026
AI-102T00-A: Develop AI solutions in Azure
13 July 2026 - 17 July 2026
AI-102T00-A: Develop AI solutions in Azure
19 October 2026 - 23 October 2026
AI-102T00-A: Develop AI solutions in Azure
25 January 2027 - 29 January 2027
AI-102T00-A: Develop AI solutions in Azure

Course Content

  • 8 Modules
  • Role: Data Scientist
  • Level: Intermediate
  • Product: Azure AI Services

  • 8 Modules
  • Role: AI Engineer
  • Level: Intermediate
  • Product: Azure AI Services

  • 9 Modules
  • Role: AI Engineer
  • Level: Intermediate
  • Product: Azure AI Services

  • 8 Modules
  • Role: AI Engineer
  • Level: Intermediate
  • Product: Azure AI Services

  • 5 Modules
  • Role: AI Engineer
  • Level: Intermediate
  • Product: Azure AI Services

FAQs

The course is designed for AI engineers, software developers, cloud engineers, solution architects, and technical professionals responsible for building and deploying AI solutions on Azure.

The course covers Azure AI Foundry, Azure OpenAI Service, Azure Cognitive Services, Azure AI Search, Azure Machine Learning, and document intelligence solutions.

Participants learn how to optimise AI workloads for scalability, latency, cost efficiency, and reliability using Azure-native monitoring, deployment, and optimisation techniques.

Yes. The course focuses heavily on API-based integration, enabling learners to embed Azure AI services into web, mobile, and enterprise applications.

The course emphasises architectural design, maintainability, monitoring, and ethical AI practices, ensuring solutions are production-ready and suitable for enterprise environments.

This course prepares learners for the Microsoft Azure AI Engineer Associate (AI-102) certification and supports career progression in AI engineering, cloud solution development, and advanced data-driven roles.