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Microsoft AI-300 Exam Syllabus Topics:

Microsoft Operationalizing Machine Learning and Generative AI Solutions Sample Questions:

1. A Retrieval-Augmented Generation (RAG) solution returns incomplete answers because relevant content is inconsistently retrieved from the knowledge source.
You need to improve RAG accuracy without changing the embedding model currently in use. You need to achieve this goal while minimizing operational costs.
Which two actions should you perform? Each correct answer presents part of the solution.
Choose two.
NOTE: Each correct selection is worth one point.

A) Increase token limits for all requests.
B) Implement an optimized re-ranker.
C) Optimize the length of embedding vectors.
D) Tune chunk size and overlap to match content structure.

2. A pipeline step fails intermittently due to transient compute issues. You need to improve reliability without modifying core logic or increasing cost significantly. What is the BEST approach?

A) Increase compute size
B) Enable retry policy on pipeline step
C) Run pipeline manually
D) Remove failing step

3. A real-time endpoint experiences sporadic latency spikes. Investigation reveals instances scale down to zero during inactivity. You need to reduce latency without significantly increasing cost.
What should you configure?

A) Set minimum instance count
B) Reduce logging
C) Switch to batch endpoint
D) Increase timeout settings

4. Hotspot Question
A company is creating an internal tool that summarizes long meeting transcripts and extracts action items.
The model must:
- Process text inputs up to 200k tokens long.
- Generate concise summaries in seconds.
- Support interactive testing before integration into the app.
You need to select, deploy, and test a model that supports summarization with low latency.
How should you complete the configuration plan? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

5. You deploy a model to production but do not have labeled data available for evaluating prediction accuracy. However, you must monitor model health continuously. What is the BEST strategy?

A) Use data drift detection
B) Monitor accuracy metrics
C) Perform manual evaluation only
D) Disable monitoring

Solutions: