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

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

At a glance

• Level: Intermediate

• Product: Azure

• Role: AI Engineer

• Duration: 5 days

• Language: Serbian (English)

• Certification: Microsoft Certified: Azure AI Engineer Associate (Exam AI-102)

Audience Profile

This course is designed for software engineers proficient in C# or Python who want to build, manage, and deploy AI solutions using Azure AI services, including Cognitive Services, AI Foundry, AI Search, and Azure OpenAI. Experience with REST APIs and SDKs is recommended.

Skills You’ll Gain

• Plan and manage AI solutions in Azure

• Implement generative AI applications and AI agents

• Use Computer Vision, Language, Speech, and AI Search services

• Build and support chatbots and conversational agents

• Apply responsible AI practices, including security and monitoring

• Use containers, prompt engineering, and Retrieval-Augmented Generation (RAG)

• Leverage Azure OpenAI Service and AI Foundry tools

Course Modules

1. Introduction to AI and Azure AI services
   Learn the fundamentals of AI and explore the Azure AI services used to build intelligent cloud applications.

2. Authentication and security for Azure AI services
   Understand how to securely access Azure AI services using authentication, API keys, and role-based access control.

3. Computer Vision with Azure AI Vision
   Discover image analysis, facial recognition, OCR, and video processing using Azure AI Vision.

4. Language understanding and text analytics (Azure AI Language)
   Extract insights from text with sentiment analysis, entity recognition, translation, and custom text classification.

5. Conversational AI and chatbots
   Build intelligent virtual assistants using Azure Bot Service and Language Understanding to provide natural user interactions.

6. Question answering with Azure AI
   Create custom knowledge bases and question-answering solutions for efficient information retrieval.

7. Speech recognition and synthesis
   Implement speech-to-text, text-to-speech, and speech translation features for accessible and interactive applications.

8. Information extraction and prompt engineering using Azure OpenAI
   Leverage Azure OpenAI to generate text and code, perform advanced reasoning, and design effective prompts.

9. Building and deploying generative AI applications
   Develop generative AI apps with Retrieval-Augmented Generation (RAG), copilots, and compliance best practices.

10. Implementing an AI agent
    Combine vision, language, and speech services to create intelligent agents simulating human-like interactions.

11. Knowledge mining and information extraction (Azure AI Search)
    Build solutions that extract structured data from unstructured content and enable semantic search experiences.

12. Responsible AI practices and model interpretability
    Apply Microsoft’s Responsible AI principles to ensure fairness, transparency, and explainability in AI solutions.

13. Monitoring, troubleshooting, and lifecycle management
    Learn to monitor, retrain, and maintain AI models using MLOps best practices for continuous improvement.

This training prepare you for official Microsoft Exam AI-102: Designing and Implementing a Microsoft Azure AI Solution.