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Microsoft Operationalizing Machine Learning and Generative AI Solutions Sample Questions:
1. You need to run large-scale inference jobs on millions of records periodically. Jobs are not latency-sensitive but must be cost-efficient and scalable. Which deployment option is MOST appropriate?
A) Batch endpoint
B) Managed online endpoint
C) Local endpoint
D) Notebook execution
2. Drag and Drop Question
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.
3. An organization is deploying several generative AI workloads by using Microsoft Foundry. Each workload must meet different requirements related to data governance, task specialization, and operational cost control.
The organization requires models that meet the following requirements:
- Model behavior aligns with the task being performed.
- Data handling aligns with internal governance policies.
- Operational complexity and cost are justified by workload needs.
You need to select the foundation model options that meet the requirements.
Which three models can you select? Each correct answer presents a complete solution. Choose three.
NOTE: Each correct selection is worth one point.
A) A model that offers enterprise governance controls when workloads process regulated business data
B) A model that is optimized for conversational reasoning when deploying an interactive assistant
C) A model that supports multiple input types when workloads require combined text and image analysis
D) The smallest available model to minimize the usage cost
E) The largest available model to simplify operational management
4. 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.
5. 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?
A) UTF-8
B) ASCII
C) ISO-8859-1
D) UTF-16
Solutions:
| Question # 1 Answer: A | Question # 2 Answer: Only visible for members | Question # 3 Answer: A,D,E | Question # 4 Answer: Only visible for members | Question # 5 Answer: A |





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