DP-100 Question #238: Real Exam Question with Answer & Explanation

Question

You use the Azure Machine Learning Python SDK to define a pipeline to train a model. The data used to train the model is read from a folder in a datastore. You need to ensure the pipeline runs automatically whenever the data in the folder changes. What should you do?

Options

• ASet the regenerate_outputs property of the pipeline to True
• BCreate a ScheduleRecurrance object with a Frequency of auto. Use the object to create a
• CCreate a PipelineParameter with a default value that references the location where the training
• DCreate a Schedule for the pipeline. Specify the datastore in the datastore property, and the folder

Explanation

{"question_number": 1, "correct_answer": "D", "explanation": "To trigger a pipeline automatically when data changes in a specific datastore folder, you create a Schedule object and set its datastore property to the monitored datastore and the path_on_datastore property to the specific folder. Azure ML polls that path and triggers the pipeline whenever new or modified files are detected. Option A (regenerate_outputs=True) forces step re-execution regardless of data changes but does not create an automatic trigger. Option B is invalid because Frequency has no 'auto' value. Option C (PipelineParameter) parameterizes pipeline inputs but does not create an event-driven trigger.", "generated_by": "claude-sonnet", "llm_judge_score": 3}

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