Microsoft Certified: Azure AI Apps and Agents Developer Associate
Exam overview, official domain weights and free sample questions. Subscribers get 230 practice questions, 97 flashcards, 2 labs, a study guide and video lessons for this exam.
Exam at a glance
- Exam code
- AI-103
- Questions
- not published
- Time
- 120 minutes
- Question types
- multiple choice and other formats. May include interactive components (exact types not published)
- Passing score
- 700
- Exam fee
- Price depends on the country or region where the exam is proctored (exam page). Microsoft's price sheet lists US $165 for role-based exams in the United States
- Delivery
- online proctored or test center (Pearson VUE)
- Prerequisites
- None. Recommended: experience building apps in Python, and familiarity with generative AI and Azure
- Renewal
- Expires annually. Renew with a free online assessment on Microsoft Learn
- Version notes
- Replaces AI-102, which retired Jun 30, 2026. No AI-103 retirement date published
From the official exam page (checked 2026-11-09). Always confirm details with the vendor: official exam page, official objectives.
Domains and weights
- 1.1 Choose the appropriate Foundry services for generative AI and agents
- 1.2 Set up AI solutions in Foundry
- 1.3 Manage, monitor, and secure AI systems
- 1.4 Implement responsible AI across generative AI and agentic systems
- 2.1 Build generative applications by using Foundry
- 2.2 Build agents by using Foundry
- 2.3 Optimize and operationalize generative AI systems
- 3.1 Design and implement image- and video-generation solutions
- 3.2 Design and implement multimodal understanding workflows
- 3.3 Implement responsible AI for multimodal content
- 4.1 Apply language model text analysis
- 4.2 Implement speech solutions
- 5.1 Build retrieval and grounding pipelines
- 5.2 Extract content from documents
Free sample questions
Original questions in the style of the exam. Pick an answer to see the explanation.
A help-desk app must classify 2 million short tickets per day into 12 categories at the lowest cost, with acceptable accuracy already demonstrated by a small model. Which model choice is best?
A Python app must call a chat model deployed in a Foundry project using the project endpoint and Entra ID authentication. What should the code use?
A retailer wants to generate lifestyle product images from text prompts plus a reference photo of the product. Which capability should be used?
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