Microsoft Operationalizing Machine Learning and Generative AI Solutions - AI-300

Microsoft AI-300 test insides dumps
  • Exam Code: AI-300
  • Exam Name: Operationalizing Machine Learning and Generative AI Solutions
  • Updated: May 30, 2026
  • Q & A: 77 Questions and Answers
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Microsoft Operationalizing Machine Learning and Generative AI Solutions Sample Questions:

1. You manage a Microsoft Foundry project. You build a multi-turn chatbot application.
You plan to filter your traces to identify issues while observing how the application is responding.
The solution must not use an external knowledge base.
You need to select an evaluation metric.
Which built-in evaluator should you use?

A) CoherenceEvaluator
B) RelevanceEvaluator
C) QAEvaluator
D) SimilarityEvaluator


2. Your model requires access to external APIs using sensitive credentials during inference. You must ensure credentials are not exposed in code, logs, or environment variables. What should you implement?

A) Encrypt credentials locally
B) Hardcode credentials
C) Use Azure Key Vault with managed identity
D) Store in config files


3. 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?

A) Configure content filters.
B) Apply a blocklist.
C) Generate synthetic interaction data.
D) Enable observability metrics.


4. 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?

A) TSV
B) JSONL
C) JSON
D) CSV


5. Hotspot Question
A team trains an MLflow model that scores customer churn risk. The model will be consumed by different downstream systems.
One system requests predictions synchronously during customer interactions.
Another system submits files containing millions of records for scheduled scoring.
You need to deploy the model by using managed inference options that match each usage pattern.
Which option should you use for each usage pattern? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.


Solutions:

Question # 1
Answer: A
Question # 2
Answer: C
Question # 3
Answer: C
Question # 4
Answer: B
Question # 5
Answer: Only visible for members

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