- A
Use Azure AI Vision Image Analysis with a pre-built model
Why wrong: Pre-built models are not tailored to specific defect categories and would not perform well with only two custom classes.
- B
Use Azure AI Custom Vision with image classification
Custom Vision with transfer learning is ideal for small datasets and binary classification tasks like defect detection.
- C
Use Azure AI Custom Vision with object detection
Why wrong: Object detection is for locating objects in an image, not binary classification of the whole image.
- D
Train a deep learning model from scratch using Azure Machine Learning
Why wrong: Training from scratch requires a large dataset (typically thousands of images per class) and is not efficient with only 500 images per class.
Question 260 of 993
AI-102 Implement computer vision solutions Practice Question
This AI-102 practice question tests your understanding of implement computer vision solutions. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
You are developing a solution to detect defects on a manufacturing assembly line using computer vision. The solution must classify images as 'defective' or 'non-defective'. You have a limited set of labeled images (500 per class). Which approach should you recommend?
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Use Azure AI Custom Vision with image classification
Azure AI Custom Vision with image classification is the best choice because it allows you to fine-tune a pre-trained deep learning model on your limited dataset (500 images per class) to classify images as 'defective' or 'non-defective'. This approach requires minimal data and expertise compared to training from scratch, and it is specifically designed for custom classification tasks with small datasets.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Use Azure AI Vision Image Analysis with a pre-built model
Why it's wrong here
Pre-built models are not tailored to specific defect categories and would not perform well with only two custom classes.
- ✓
Use Azure AI Custom Vision with image classification
Why this is correct
Custom Vision with transfer learning is ideal for small datasets and binary classification tasks like defect detection.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Use Azure AI Custom Vision with object detection
Why it's wrong here
Object detection is for locating objects in an image, not binary classification of the whole image.
- ✗
Train a deep learning model from scratch using Azure Machine Learning
Why it's wrong here
Training from scratch requires a large dataset (typically thousands of images per class) and is not efficient with only 500 images per class.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates may confuse image classification (assigning a single label to the whole image) with object detection (locating objects), or assume that a pre-built model can be retrained for custom classes, when in fact Azure AI Custom Vision is the correct service for custom classification with limited data.
Detailed technical explanation
How to think about this question
Azure AI Custom Vision uses transfer learning, where a pre-trained convolutional neural network (e.g., ResNet) is fine-tuned on your custom dataset. This leverages learned features from millions of images, enabling high accuracy with as few as 50 images per class, though 500 per class is ideal for robust performance. The service automatically handles image preprocessing, augmentation, and model selection, making it accessible without deep learning expertise.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
What to study next
Got this wrong? Here's your next step.
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FAQ
Questions learners often ask
What does this AI-102 question test?
Implement computer vision solutions — This question tests Implement computer vision solutions — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Use Azure AI Custom Vision with image classification — Azure AI Custom Vision with image classification is the best choice because it allows you to fine-tune a pre-trained deep learning model on your limited dataset (500 images per class) to classify images as 'defective' or 'non-defective'. This approach requires minimal data and expertise compared to training from scratch, and it is specifically designed for custom classification tasks with small datasets.
What should I do if I get this AI-102 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
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Last reviewed: Jul 4, 2026
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