Microsoft AI-300 - Operationalizing Machine Learning and Generative AI Solutions Exam
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Total 60 questions
Question #6 (Topic: Topic 1, Design and implement an MLOps infrastructure
)
You have a deployment of an Azure OpenAI Service base model.
You plan to fine-tune the model.
You need to prepare a file that contains training data.
Which file format should you use?
You plan to fine-tune the model.
You need to prepare a file that contains training data.
Which file format should you use?
A. CSV
B. TSV
C. JSONL
D. JSON
Answer: C
Question #7 (Topic: Topic 1, Design and implement an MLOps infrastructure
)
You have a deployment of an Azure OpenAI Service base model.
You plan to fine-tune the model.
You need to prepare a file that contains training data for multi-turn chat.
Which file encoding method should you use?
You plan to fine-tune the model.
You need to prepare a file that contains training data for multi-turn chat.
Which file encoding method should you use?
A. ISO-8859-1
B. UTF-16
C. UTF-8
D. ASCII
Answer: C
Question #8 (Topic: Topic 1, Design and implement an MLOps infrastructure
)
You are fine-tuning a base language model to analyze customer feedback.
You label examples of support tickets. You must improve classification accuracy by configuring and fine-tuning the base model in Microsoft Foundry.
You need to configure and run fine-tuning.
What should you do first?
You label examples of support tickets. You must improve classification accuracy by configuring and fine-tuning the base model in Microsoft Foundry.
You need to configure and run fine-tuning.
What should you do first?
A. Use prompt flow to generate multiple prompt templates for evaluation.
B. Deploy the base model to an online endpoint before starting fine-tuning.
C. Enable tracing for all inference calls in the evaluation pipeline.
D. Format the dataset as a JSONL file with prompt-completion pairs and upload the file.
Answer: C
Question #9 (Topic: Topic 1, Design and implement an MLOps infrastructure
)
A team is working in Microsoft Foundry to test and compare large language model (LLM) prompt variants in a development environment.
The team requires consistent inputs to evaluate prompt variants without relying on live user traffic.
You need to create a controlled evaluation of input data.
Which action should you perform first?
The team requires consistent inputs to evaluate prompt variants without relying on live user traffic.
You need to create a controlled evaluation of input data.
Which action should you perform first?
A. Generate synthetic interaction data.
B. Configure content filters.
C. Apply a blocklist.
D. Enable observability metrics.
Answer: A
Question #10 (Topic: Topic 1, Design and implement an MLOps infrastructure
)
DRAG DROP
A team maintains Infrastructure as Code (IaC) templates to provision Azure Machine Learning resources.
Provisioning must be triggered by changes in the templates and executed without manual intervention.
You need to automate resource provisioning.
Which action should you take for each requirement? To answer, move the appropriate actions to the correct requirements. You may use each action once, more than once, or not at all. You may need to move the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.
A team maintains Infrastructure as Code (IaC) templates to provision Azure Machine Learning resources.
Provisioning must be triggered by changes in the templates and executed without manual intervention.
You need to automate resource provisioning.
Which action should you take for each requirement? To answer, move the appropriate actions to the correct requirements. You may use each action once, more than once, or not at all. You may need to move the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.
Answer: 
