AI-102T00 Develop AI solutions in Azure
AI-102: Develop AI solutions in Azure is intended for software developers wanting to build AI infused applications that leverage Azure AI Foundry and other Azure AI services. Topics in this course include developing generative AI apps, building AI agents, and solutions that implement computer vision and information extraction.
Plan and Manage Azure AI Solutions
Select appropriate Azure AI services for workloads.
Apply deployment strategies with CI/CD.
Implement security and monitoring for AI solutions.
Ensure Responsible AI practices (fairness, privacy, compliance).
Implement Generative AI Solutions
Develop and deploy applications with Azure OpenAI Service.
Design prompt flows and implement RAG patterns.
Apply tuning, tracing, and orchestration with Azure AI Foundry and Semantic Kernel.
Develop Computer Vision Solutions
Use Azure AI Vision for image/video analysis, object detection, and facial recognition.
Build custom computer vision models.
Implement OCR for text extraction from images and documents.
Develop Natural Language and Speech Solutions
Implement text analytics, sentiment analysis, and PII detection.
Build speech-to-text and text-to-speech applications.
Create conversational AI and QnA systems with Azure AI Language and Bot Service.
Build Knowledge Mining and Information Extraction Solutions
Create intelligent search solutions with Azure AI Search.
Implement semantic and vector search capabilities.
Develop information extraction pipelines with Document Intelligence and OCR.
This course was designed for software engineers concerned with building, managing and deploying AI solutions that leverage Azure AI Foundry and other Azure AI services. They are familiar with C# or Python and have knowledge on using REST-based APIs and SDKs to build generative AI, computer vision, language analysis, and information extraction solutions on Azure.
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
Recommended course prerequisites
- AI-900T00: Microsoft Azure AI Fundamentals course
Introduction to AI and Azure AI services
Azure AI Foundry overview, developer tools, and SDKs
Responsible AI principles
Explore and deploy models from the catalog
Optimize model performance
Use the Azure AI Foundry SDK to build apps
Introduction to Prompt Flow lifecycle and monitoring
Grounding language models with custom data
Build RAG-based applications
Implement RAG in Prompt Flow
Fine-tune chat completion models in Azure AI Foundry
Plan, measure, and mitigate potential harms
Manage responsible generative AI solutions
Evaluate model performance (manual and automated)
Introduction to AI agents and Azure AI Foundry Agent Service
Develop and extend agents with custom tools
Build Semantic Kernel agents and add plugins
Use Semantic Kernel for multi-agent solutions (group chat, selection, termination strategies)
Develop connected multi-agent solutions with Agent Service
Integrate MCP tools with Azure AI agents
Text analysis: key phrases, sentiment, entities
Conversational AI: QnA knowledge bases, multi-turn dialogues
Conversational Language Understanding: intents, utterances, entities
Custom text classification and named entity recognition
Azure AI Translator for text translation
Speech-to-text, text-to-speech, and synthesis markup
Speech translation
Build audio-enabled generative AI applications
Azure AI Vision image analysis and OCR
Face detection, analysis, and recognition with Responsible AI considerations
Custom Vision: image classification and object detection
Video analysis with Azure Video Indexer
Vision-enabled generative AI applications
Image generation models in Azure AI Foundry
Azure AI Content Understanding and REST API
Build multimodal analysis client applications
Use prebuilt Document Intelligence models
Extract structured data from forms and train custom models
Build knowledge mining solutions with Azure AI Search