How should I use these Computer Vision practice questions?

Read each scenario carefully and choose your answer before revealing the explanation. Then check why your choice was right or wrong. Repeat until the reasoning feels automatic.

Can I practise just Computer Vision questions in a focused session?

Yes — use the session launcher on this page to start a 10-, 20-, 30- or 50-question session drawn entirely from the Computer Vision domain.

AI-103 · topic practice

Computer Vision practice questions

Practise Microsoft Certified: Azure AI Apps and Agents Developer Associate (AI-103) (AI-103) Computer Vision practice questions — original exam-style scenarios with answer choices, explanations, and analysis of common mistakes.

Courseiva uses original exam-style practice questions designed for learning and revision. The goal is to understand the concepts, recognise exam patterns, and improve through explanations — not memorise copied exam dumps.

Reviewed byJohnson Ajibi· MSc IT Security

20 questionsDomain: Computer Vision

Practice 10 questions Browse domain →

What the exam tests

What to know about Computer Vision

Computer Vision 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.

Watch out for

Common Computer Vision exam traps

▸Answering from memory before reading the full scenario.
▸Missing a constraint such as cost, availability, security, scope or command context.
▸Choosing a broad answer when the question asks for the most specific fix.
▸Ignoring why the wrong options are tempting.

Practice set

Computer Vision questions

20 questions · select your answer, then reveal the explanation

Question 1mediummultiple choice

Read the full Computer Vision explanation →

You are integrating Azure AI Vision Read API into a high-throughput workflow. You receive an HTTP 202 Accepted response. What action should your application take next?

Trap 1: Switch to synchronous Read API endpoint.

Image Analysis 4.0 Read is an asynchronous operation.

Trap 2: Parse the response body directly for the extracted text results.

An HTTP 202 response body does not contain the final OCR payload.

Trap 3: Immediately retry the POST request with an increased timeout value.

Retrying the initial POST will start a new job instead of checking the existing one.

Computer Vision practice questions

What to know about Computer Vision

Common Computer Vision exam traps

Computer Vision questions

You are integrating Azure AI Vision Read API into a high-throughput workflow. You receive an HTTP 202 Accepted response. What action should your application take next?

You are training a Custom Vision object detection model to identify specific manufacturing defects on a production line. You have uploaded 50 images and tagged the defects. When you attempt to train the model, the training fails. What is the most likely cause?

You have trained a Custom Vision classification model. You need to export the model to run locally on an edge device using ONNX format. Which project domain must you select when creating the project to support export?

You are developing a .NET application that extracts bounding boxes of text from scanned documents using Azure AI Vision 4.0. Which asynchronous API operation should you call first to initiate the OCR process?

Your company wants to generate descriptive captions for thousands of product images automatically using Azure AI Vision. Which visual feature parameter should you specify in the analyze request?

You need to determine the primary dominant colors and whether an image is predominantly black-and-white using Azure AI Vision. Which visual feature parameter provides this information?

Your application uploads an image to Azure AI Vision for analysis. You need to generate thumbnail images with specific aspect ratios while maintaining the primary region of interest. Which API endpoint or feature should you use?

You are building a content moderation pipeline. You need to detect if user-uploaded images contain adult content, racy content, or gore using Azure AI Vision. Which feature should you include?

Your enterprise application uses Custom Vision. Due to compliance policies, you must ensure that your training data and model endpoints reside within a specific Azure region with strict data residency guarantees. Which resource configuration should you use?

You are designing a multimodal solution that combines Azure AI Vision dense captions with Azure OpenAI GPT-4 Vision. You want to extract precise bounding box coordinates for multiple objects in complex scenes and pass them as structured context. Which API feature should you invoke?

You are writing a Python script using the Azure AI Vision SDK to analyze an image from a local file path. Which client class should you instantiate first?

Your application analyzes high-resolution engineering blueprints using Azure AI Vision Read API. Users report that small text annotations are occasionally missed. How can you optimize the input image or API configuration to improve recognition of small text?

You are evaluating a Custom Vision classification model. You want to programmatically test the model against a validation dataset without using the portal UI. Which endpoint should your script call?

Your application uploads images to Azure AI Vision via URLs. One of your URLs is failing with an invalid image error, even though the image opens correctly in web browsers. What is the most likely reason?

You need to retrieve coordinates of people detected in an image using Azure AI Vision 4.0. Which visual feature should you request?

You are troubleshooting a Custom Vision object detection model that has low precision and high false-positive rates for a specific object class. During data analysis, you notice that negative images (images without the object) lack background variety. What is the recommended remediation step?

You are building an automated asset management system that processes millions of images annually. To optimize costs and latency, you want to minimize the number of API calls while extracting tags, bounding box objects, and OCR text simultaneously. How should you structure your API request?

You are deploying a Custom Vision object detection model as a Docker container on an Azure Kubernetes Service (AKS) cluster. During load testing, you notice high memory consumption and container restarts. Which configuration setting in the deployment manifest should you review to ensure stability?

You are using Azure AI Vision to analyze an image. You want to receive the output in Spanish instead of English. Which query parameter should you add to your request?

When creating a new project in the Custom Vision portal, you need to choose a classification type. You want to tag an image with multiple independent tags (e.g., 'outdoor', 'sunset', 'mountain'). Which classification type should you select?

Track your progress over time

Start a Computer Vision only practice session

Related AI-103 topic practice pages

Implement Generative AI And Agentic Solutions practice questions

Text Analysis practice questions

Information Extraction practice questions

Plan And Manage AN Azure AI Solution practice questions

Computer Vision practice questions

AI-103 fundamentals practice questions

AI-103 scenario practice questions

AI-103 troubleshooting practice questions

Frequently asked questions

Track your progress

Study resources

Exam traps to avoid