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Hard Difficulty Questions

Practise Microsoft Azure AI Engineer Associate AI-102 practice questions — original exam-style scenarios covering every exam domain, with detailed explanations, wrong-answer analysis, and common exam traps.

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AI-102
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Microsoft
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Scenario guide

How to approach hard difficulty questions

These are the questions most candidates get wrong. They require connecting multiple concepts, reading tricky output, or knowing edge-case behaviour that isn't on most study cards. Practising them trains you to operate under uncertainty — a necessary skill on the real exam.

Quick answer

Hard Difficulty Questions questions test whether you can apply the concept in context, not just recognise a definition.

How the topic appears in realistic exam-style scenarios.

Which detail in the question changes the correct answer.

How to eliminate plausible but wrong options.

How to connect the question back to the wider exam objective.

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Practice set

Practice scenarios

Question 1hardmulti select
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A developer is using Azure OpenAI to generate code snippets. The developer needs to ensure that the generated code does not contain security vulnerabilities. Which TWO actions should the developer take? (Choose two.)

Question 2hardmultiple choice
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A security company uses Azure Video Analyzer on IoT Edge to detect intrusions. The edge device has limited compute and network. They need to reduce latency. What should they configure?

Question 3hardmultiple choice
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A company uses Azure Face API to detect faces in a crowd. They need to comply with GDPR and delete face data after 30 days. What should they implement?

Question 4hardmultiple choice
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A financial services company is building an agent that uses Azure OpenAI to generate investment advice. The agent must be monitored for toxicity and bias. Which combination of services should the team use to implement content safety monitoring?

Question 5hardmulti select
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An agent uses Azure OpenAI with function calling to perform actions. The agent is not executing functions correctly. Which THREE factors should the team check to diagnose the issue?

Question 6hardmultiple choice
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A healthcare provider uses Azure Video Analyzer for Media to extract insights from surgical videos. They need to ensure that no patient health information (PHI) is stored in the transcriptions. What is the best approach?

Question 7hardmulti select
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Which THREE are required to build a custom video indexing solution using Azure Video Analyzer for Media? (Choose three.)

Question 8hardmultiple choice
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A company is using Azure OpenAI Service to power a customer support agent. The agent sometimes generates incorrect information when it cannot find an answer in the knowledge base. The team wants to ensure the agent only responds using information from the knowledge base and explicitly states when it does not know the answer. Which configuration should the team use?

Question 9hardmulti select
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An agent uses Azure AI Language to perform sentiment analysis on customer feedback. The team notices that the sentiment scores are sometimes inaccurate for negative feedback. Which TWO improvements should the team consider?

Question 10hardmultiple choice
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A company plans to use Azure Cognitive Search to index a large number of PDF documents stored in Azure Blob Storage. The documents contain sensitive personally identifiable information (PII). The search results should only be accessible to authorized users based on their Azure Active Directory (Azure AD) group membership. Which combination of features should the company implement?

Question 11hardmultiple choice
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A company is using Azure Cognitive Service for Language to analyze customer support transcripts. They want to identify custom categories (e.g., 'billing', 'technical support') using a custom text classification model. After training and deploying the model, they receive many false positives for the 'billing' category. What is the best first step to improve model accuracy?

Question 12hardmultiple choice
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You are an AI engineer at a healthcare company. The company uses Azure Cognitive Services to process medical records. They have a Computer Vision resource deployed in the East US region. Recently, they implemented a custom vision model for detecting specific anomalies in X-ray images. The model was trained using the Custom Vision portal and exported as a TensorFlow model. They deployed the model to an Azure Kubernetes Service (AKS) cluster using a Docker container. The container runs the model and exposes a REST API endpoint for inference. The endpoint is used by a web application that is also hosted in the same AKS cluster. The web application is experiencing high latency when making inference requests. The latency spikes up to 10 seconds during peak hours. The AKS cluster has autoscaling enabled based on CPU metrics. The container's resource limits are set to 1 CPU core and 2 GB memory. The model's inference time on a single image is approximately 500 ms on the development machine. The team has not changed the model or the application code recently. The number of concurrent users has increased by 50% in the last month. What should you do to reduce inference latency?

Question 13hardmultiple choice
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A hospital uses Azure Cognitive Service for Language to extract medical entities from clinical notes. The extraction accuracy for medication names and dosages is low. The engineer needs to improve performance without adding new training data. Which solution should the engineer implement?

Question 14hardmultiple choice
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A company uses Azure OpenAI to generate product descriptions. They notice that the model occasionally produces descriptions that include false claims about product features. The company needs to reduce the frequency of these inaccuracies without changing the training data. Which parameter adjustment would be most effective?

Question 15hardmulti select
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A company is designing a solution that uses Azure Cognitive Services for text analytics. The solution must meet the following requirements: - Detect sentiment in customer feedback. - Extract key phrases from the feedback. - Identify the language of the feedback automatically. - Ensure that the solution can scale to handle thousands of requests per second. Which TWO actions should the company take?

Question 16hardmulti select
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A company uses Azure Content Moderator to moderate user-generated content. They need to ensure that content moderation workflows comply with regional regulations. Which TWO actions should they take?

Question 17hardmultiple choice
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An image was submitted to Azure Content Moderator's Image Moderation API. The application uses a threshold of 0.5 for Category1 (adult) to trigger a review. Based on the exhibit, what should the application do with this image?

Exhibit

Refer to the exhibit.

```json
{
  "Classification": {
    "ReviewRecommended": false,
    "Category1": {
      "Score": 0.99
    },
    "Category2": {
      "Score": 0.02
    },
    "Category3": {
      "Score": 0.01
    }
  },
  "Terms": []
}
```

The above JSON is the output from Azure Content Moderator's Image Moderation API for an image. The application uses a threshold of 0.5 for Category1 (adult) to trigger a review.
Question 18hardmulti select
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A company uses Azure Document Intelligence to extract data from tax forms. They need to improve accuracy for a specific field. Which TWO actions should they take?

Question 19hardmulti select
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Which THREE components are required to build a custom named entity recognition (NER) model in Azure Cognitive Service for Language?

Question 20hardmulti select
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A company uses Azure Cognitive Search to index customer support emails. They need to implement a custom skill that extracts the sentiment of the email body and also identifies the primary product mentioned. The custom skill is a Python function deployed as an Azure Function. They want to ensure the skill can process multiple documents concurrently and handle errors gracefully. Which THREE configurations should they apply?

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