AI-103

Azure AI App and Agent Developer Associate

Microsoft Certified: Azure AI App and Agent Developer Associate

PS academy:/courses> Get-Certification -Id AI-103 | Select-Object -ExpandProperty Overview

40–60

Questions

~100 min

Duration

700

Passing score / 1000

5

Domains

Associate

Level

PSacademy:/courses/ai-103> Get-DomainWeights | Format-Chart

Implement Generative AI and Agentic Solutions

30–35% of exam

Plan and Manage Azure AI Solutions

25–30% of exam

Implement Computer Vision Solutions

10–15% of exam

Implement Text Analysis Solutions

10–15% of exam

Implement Information Extraction Solutions

10–15% of exam

PSacademy:/courses/ai-103> Get-LearningModules -Cert AI-103

MOD 01

Generative AI and Agentic Solutions

LLM deployment and management in Azure AI Foundry
Prompt engineering: system prompts, few-shot, chain-of-thought
RAG architecture: chunking, embedding, indexing, retrieval
Agent design with function calling, code interpreter, file search
Multi-agent orchestration with Semantic Kernel and Agent Service
Agent tracing, monitoring, and evaluation frameworks

MOD 02

Plan and Manage Azure AI Solutions

Microsoft Foundry: hubs, projects, model catalog, and deployment types
PTU vs. serverless provisioning and quota management
CI/CD pipelines for AI solutions with GitHub Actions
Content filters, Prompt Shields, and responsible AI safeguards
Security: managed identity, RBAC, and private endpoints for AI services
Cost management, monitoring, and AI performance observability

MOD 03

Computer Vision Solutions

Azure AI Vision: image analysis, object detection, OCR features
Image and video generation with DALL-E and GPT-4o multimodal
Content safety filters and watermarking for generated images
Custom vision models and domain adaptation
Multimodal analysis combining text and image inputs
Prompt injection mitigation for vision pipelines

MOD 04

Text Analysis Solutions

Azure AI Language: entity recognition, sentiment, key phrase extraction
Language translation and custom NER/classification models
Azure AI Speech: STT, TTS, and real-time transcription
Speech integration in agent interaction pipelines
Conversational language understanding (CLU) and QnA
Domain customization and model fine-tuning for text tasks

MOD 05

Information Extraction Solutions

Azure Document Intelligence: prebuilt and custom extraction models
Azure AI Search: vector, semantic, and hybrid search modes
Indexing pipelines and AI enrichment skill sets
Knowledge stores and grounded representations for RAG
Structured content extraction from forms, invoices, and contracts
Indexer scheduling, incremental enrichment, and cache reset

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