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| Certification Vendor: | Microsoft |
|---|---|
| Exam Name: | Developing AI Apps and Agents on Azure AI |
| Exam Number: | AI-103 |
| Real Exam Qty: | 40-60 |
| Passing Score: | 700/1000 |
| Related Certifications: | Microsoft Certified: Azure Developer Associate Microsoft Certified: Azure AI Engineer Associate Microsoft Certified: Azure AI Fundamentals |
| Exam Price: | USD 165 (may vary by region) |
| Certificate Validity Period: | 1 year (renewable via Microsoft Learn assessment) |
| Available Languages: | English |
| Exam Format: | Scenario-based questions, Drag and drop, Case studies, Multiple response, Multiple choice |
| Exam Duration: | 120-180 |
| Recommended Training: | Microsoft Learn - Azure AI Engineer Learning Path Azure OpenAI Service Documentation |
| Exam Registration: | Microsoft Certification Dashboard Pearson VUE Microsoft Exams |
| Sample Questions: | ![]() |
| Exam Way: | Online proctored exam or authorized test center |
| Pre Condition: | Recommended: experience with Azure services, Python or C#, and basic machine learning concepts. Prior knowledge of Azure AI-102 or equivalent is helpful but not mandatory. |
| Official Syllabus URL: | https://learn.microsoft.com/en-us/credentials/certifications/azure-ai-engineer/ |
| Section | Objectives |
|---|---|
| Implement Computer Vision Solutions | - Image classification and object detection - OCR and document intelligence |
| Develop Generative AI Applications and Agents | - AI agents architecture
|
| Plan and Manage Azure AI Solutions | - Responsible AI principles and governance - Model selection and lifecycle management - Azure AI resource provisioning and configuration |
| Implement Natural Language Processing Solutions | - Language understanding and intent recognition - Text analytics and summarization - Translation and multilingual support |
| Knowledge Mining and Information Retrieval | - Azure AI Search configuration - Indexing and semantic search - RAG (Retrieval Augmented Generation) patterns |
Microsoft specifies the following prerequisites for the Microsoft Developing AI Apps and Agents on Azure: Recommended: experience with Azure services, Python or C#, and basic machine learning concepts. Prior knowledge of Azure AI-102 or equivalent is helpful but not mandatory..
Confirm the authoritative details on the official certification page before you register.
As of the latest information, the passing score for the AI-103 exam is 700/1000 and the fee is USD 165 (may vary by region). Microsoft sets both, so verify the current figures on the official site before scheduling.
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According to the latest exam information, the AI-103 exam includes 40-60 questions and lasts 120-180 minutes. Practicing under the same limit builds the pacing confidence you will want on the day.
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Book your test center or online session early, and let a fixed date organize your preparation.
A copilot must answer multi-part questions that depend on earlier turns in the conversation. You want the system to break each complex question into focused subqueries, run them in parallel, and semantically rerank the results before composing an answer. Which Azure AI Search capability provides this?
Correct Answer: D 🗳️
Explanation: Only visible for ValidDumps members. You can sign-up / login (it's free).
Hotspot Question
You have a Microsoft Foundry project that contains an agent named PaymentAgent.
PaymentAgent includes a function tool that issues customer refunds by using an external API.
You are creating a workflow in YAML.
You need to ensure that the workflow pauses for human approval and continues with the refund step only after approval is granted.
How should you complete the workflow definition? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Correct Answer:

Hotspot Question
You have a Microsoft Foundry project that contains a customer support application.
You create an evaluation named Run1 that has the following configurations:
- Includes risk and safety metrics
- Includes the protected material evaluation
- Includes harmful content metrics that use a medium severity threshold You create an evaluation named Run2 that has the following configurations:
- Includes risk and safety metrics
- Includes the protected material evaluation
- Includes harmful content metrics that use a high severity threshold
You run both evaluations against a dataset named DB1 and receive the following results:
- Content harm defect rate of Run1: 12%
- Content harm defect rate of Run2: 4%
- Protected material evaluation of Run1: 6%
- Protected material evaluation of Run1: 6%
You start a fine-tuning job by using DB1. The job fails during automatic RAI checks for multiple content harm types.
You discover that the content filtering configuration is set to high severity.
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Correct Answer:

Explanation:
Box 1: No
Changing the content filtering configuration to low severity will not resolve the fine-tuning job issues.
Box 2: Yes
The difference between a 12% defect rate in Run1 and a 4% defect rate in Run2 is entirely consistent with the different severity thresholds configured for the two evaluations.
Box 3: Yes
The protected material evaluation metric is entirely unaffected by changes to the content harm severity threshold.
Reference:
https://learn.microsoft.com/en-us/python/api/azure-ai-evaluation/azure.ai.evaluation
Hotspot Question
You have a Microsoft Foundry project that contains a workflow for a customer support triage process.
You have an Ask a question node that stores user responses in a local variable named Var01.
You need to create the following Power Fx expressions:
- An if/else condition expression that ensures that Var01 contains a
value
- A Send message expression that returns the stored user response in
uppercase
How should you configure the expressions? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Correct Answer:

You are planning a Microsoft Foundry project named Project1 that will contain multiple agents.
Each agent will access the same Azure AI Search resource.
You need to recommend a solution to centrally manage the Azure AI Search credentials within Project1. The solution must be implemented across all the agents.
What should you recommend?
Correct Answer: D 🗳️
Explanation: Only visible for ValidDumps members. You can sign-up / login (it's free).
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