What You'll Learn

  • Choose the right models
  • Foundry services
  • retrieval methods
  • and agent tools for generative AI and multimodal workloads,Deploy
  • secure
  • and monitor Azure AI solutions with CI/CD
  • quotas
  • managed identity
  • private networking
  • and cost controls,Apply responsible AI with safety filters
  • guardrails
  • evaluations
  • trace logging
  • and governed agent tool access,Build retrieval-augmented generation apps and multistep workflows with Microsoft Foundry SDKs and connectors,Design single and multi-agent solutions with function calling
  • memory
  • tool integration
  • and approval safeguards,Implement image and video generation
  • multimodal understanding
  • and visual content safety with Content Understanding,Build text and speech solutions for extraction
  • sentiment
  • translation
  • and speech-enabled agent interactions,Create retrieval and document extraction pipelines with hybrid and vector search
  • OCR
  • and Content Understanding

Requirements

  • Experience developing applications in Python is recommended.,Basic familiarity with Azure services and the Azure portal will help with the infrastructure and security scenarios.,A general understanding of generative AI concepts such as prompts
  • embeddings
  • and retrieval is helpful but not required.,Hands-on time with Microsoft Foundry is useful. The explanations fill in the gaps as you go.,Most of all
  • you need a willingness to work through why each option is right or wrong
  • not only which one is correct.

Description

Prepare for the Microsoft AI-103 Azure AI Apps and Agents Developer Associate exam with hands-on, scenario-based practice

These AI-103 practice tests are for developers preparing for the Microsoft Certified: Azure AI Apps and Agents Developer Associate credential. The exam is also called Developing AI Apps and Agents on Azure. AI-103 replaces the retired AI-102 and is built around Microsoft Foundry. It tests whether you can choose the right models and services, build grounded generative AI apps and agents, and run them securely and responsibly in production.

Why this course

AI-103 is a developer exam about implementation choices. You need to know which model fits a task, which retrieval method grounds an agent best, how to lock down a deployment with managed identity, and how to stop a prompt injection hidden inside an image. Every question here starts from a realistic build scenario and asks for the best technical decision. All questions are original, mapped to the current skills outline, and updated as Microsoft revises the exam.

What’s inside, by exam domain

  • Planning and managing an Azure AI solution: choosing between large, small, and multimodal models; selecting Foundry services, retrieval, memory, and tools; deployment options and CI/CD; quotas, scaling, and cost; monitoring drift and grounding quality; security with managed identity and private networking; and responsible AI guardrails, evaluations, auditing, and agent oversight

  • Generative AI and agentic solutions: retrieval-augmented generation, tool-augmented and multistep workflows, Foundry SDKs, agent roles and tool schemas, function calling and memory, multi-agent orchestration, approval flows, prompt and parameter tuning, and observability with tracing and token analytics

  • Computer vision: image and video generation and editing, multimodal understanding, captions and alt text, Content Understanding for visual and video analysis, and content safety for visual inputs

  • Text analysis: generative entity, topic, and summary extraction, structured JSON outputs, sentiment and sensitive-content detection, translation, and speech-to-text and text-to-speech for agents

  • Information extraction: ingesting and indexing documents, images, audio, and video; semantic, hybrid, and vector search; enrichment skills; OCR-based ingestion; and Content Understanding analyzers for grounded, structured output

How the explanations help you learn

Every question includes a detailed explanation for every answer option. You see why the correct choice works for that scenario and why each of the other choices fails. A wrong option might be a less suitable model, a weaker retrieval strategy, a security gap, or a service that doesn’t support the feature. This builds the practical judgment AI-103 measures and that you need on real projects.

Who it’s for

  • Azure AI engineers and Python developers who build generative AI apps and agents on Azure

  • Candidates moving to AI-103 from the retired AI-102

Start practicing today

You get lifetime access, regular updates, and the protection of Udemy’s 30-day refund policy. Enroll now, find your weak domains, and go into AI-103 ready to build like an Azure AI engineer.

Disclaimer

This course is an independent, unofficial study resource. It is not affiliated with, endorsed by, or sponsored by Microsoft Corporation. Microsoft, Azure, Microsoft Foundry, and related names are trademarks of the Microsoft group of companies. They are used only to identify the exam this course helps you prepare for. All questions are original practice material and are not drawn from any Microsoft exam.

Who this course is for:

  • Candidates preparing for the Microsoft AI-103 Azure AI Apps and Agents Developer Associate exam,Azure AI engineers and Python developers who build generative AI apps and agents with Microsoft Foundry,Developers moving from the retired AI-102 exam to the new apps-and-agents certification,Software engineers moving into AI engineering who want structured
  • domain-by-domain practice,Solution builders who work with retrieval
  • document extraction
  • vision
  • or speech on Azure,Candidates retaking AI-103 who want targeted practice on their weaker domains
AI-103 Azure AI Apps and Agents Developer Practice Tests

Course Includes:

  • Price: FREE
  • Enrolled: 0 students
  • Language: English
  • Certificate: Yes
  • Difficulty: Beginner
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