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

Be thoroughly prepared for the exam and immediately learn how to develop and integrate AI solutions with Azure services.

Learning Center Microsoft Certificering AI 102

AI becomes truly valuable when it’s embedded in your applications. From smart recommendations and image recognition to generative chat functionality, Azure enables you to achieve this quickly and securely. The AI-102 certification focuses on designing, building, and managing AI solutions using Azure Cognitive Services, Azure AI Search, and Azure OpenAI. You’ll learn not just how to deploy models, but how to combine them into reliable, scalable applications.

Develop intelligent solutions with Azure AI

This certification track teaches you how to integrate AI into real-world scenarios. You’ll gain skills you can directly apply in projects, and after completion, you’ll be able to:

  • Implement AI models using Azure Cognitive Services and Azure AI Studio
  • Apply generative AI with Azure OpenAI Service
  • Retrieve and process data using Azure AI Search and RAG patterns
  • Ensure security, ethics, and governance in AI solutions
  • Successfully complete the official Microsoft AI-102 exam

What you’ll learn

The training is based on the official Microsoft exam guide and combines theory, design principles, and hands-on exercises:

  • Designing and implementing AI solutions
    • Using Azure AI Studio and Azure AI Services
    • Integrating AI into web and enterprise applications
    • Making choices between APIs, SDKs, and custom models
  • Working with Azure Cognitive Services
    • Language Services: Natural Language Processing, QnA, sentiment analysis
    • Vision Services: image classification, object detection, OCR
    • Speech Services: transcription, translation, and synthesis
    • Decision Services: personalization and anomaly detection
  • Azure AI Search and knowledge management
    • Document indexing, semantic search, and query enrichment
    • Combining Retrieval-Augmented Generation (RAG) with LLMs
  • Integration with Azure OpenAI Service
    • Designing generative applications using GPT models
    • Prompt design, system messages, and safety guidelines
    • Evaluating and improving AI output
  • Security and responsible usage
    • Identity & access management with Microsoft Entra ID
    • Secret management with Azure Key Vault
    • Principles of Responsible AI: fairness, reliability, and governance

Practical info

  • Target audience: AI engineers, software developers, data scientists, and solution architects building or integrating AI solutions in Azure
  • Level: Associate (experienced)
  • Duration: Tailored, depending on knowledge level and needs
  • Location: Remote or classroom-based
  • Materials: Official Microsoft course material, supplemented with practical cases
  • Cost: Depends on training needs and program duration

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