- A
Azure OpenAI Service
Why wrong: Azure OpenAI provides pre-trained models; you cannot train custom models from scratch.
- B
Azure Machine Learning
Azure Machine Learning supports training custom generative models using your own data.
- C
Azure AI Vision
Why wrong: Azure AI Vision is for image classification, object detection, etc., not for generative tasks.
- D
Azure AI Document Intelligence
Why wrong: This service is for document analysis and extraction, not generative model training.
Question 536 of 993
AI-102 Implement generative AI solutions Practice Question
This AI-102 practice question tests your understanding of implement generative ai 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.
Your company wants to build a custom generative AI model that generates architectural designs. The model should be trained on the company's proprietary dataset of floor plans and designs. Which Azure service should you use?
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
✓
Azure Machine Learning
Azure Machine Learning is the correct service because it provides a comprehensive platform for training custom generative AI models using your own proprietary datasets. It supports deep learning frameworks like PyTorch and TensorFlow, enabling you to build, train, and deploy a custom generative model for architectural designs, whereas Azure OpenAI Service is limited to pre-trained models and fine-tuning, not custom training from scratch.
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.
- ✗
Azure OpenAI Service
Why it's wrong here
Azure OpenAI provides pre-trained models; you cannot train custom models from scratch.
- ✓
Azure Machine Learning
Why this is correct
Azure Machine Learning supports training custom generative models using your own data.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Azure AI Vision
Why it's wrong here
Azure AI Vision is for image classification, object detection, etc., not for generative tasks.
- ✗
Azure AI Document Intelligence
Why it's wrong here
This service is for document analysis and extraction, not generative model training.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse 'fine-tuning' (offered by Azure OpenAI Service) with 'custom training from scratch' (offered by Azure Machine Learning), leading them to incorrectly select Azure OpenAI Service when the question explicitly requires training a model on proprietary data with custom architecture.
Detailed technical explanation
How to think about this question
Azure Machine Learning provides managed compute clusters, automated machine learning (AutoML), and distributed training capabilities that are essential for training large generative models like GANs or diffusion models on proprietary datasets. Under the hood, it integrates with Azure Blob Storage for data versioning and MLflow for experiment tracking, allowing you to iterate on model architectures and hyperparameters. In a real-world scenario, you would use Azure ML's Python SDK to define a custom neural network in PyTorch, train it on GPU clusters, and deploy it as a real-time endpoint for generating floor plans.
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 cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
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 generative AI solutions — This question tests Implement generative AI solutions — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Azure Machine Learning — Azure Machine Learning is the correct service because it provides a comprehensive platform for training custom generative AI models using your own proprietary datasets. It supports deep learning frameworks like PyTorch and TensorFlow, enabling you to build, train, and deploy a custom generative model for architectural designs, whereas Azure OpenAI Service is limited to pre-trained models and fine-tuning, not custom training from scratch.
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.
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Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
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Last reviewed: Jul 4, 2026
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