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| Name: | Microsoft Designing and Implementing a Data Science Solution on Azure |
| Exam Code: | DP-100 |
| Certification: | Microsoft Azure Data Scientist Associate |
| Vendor: | Microsoft |
| Total Questions: | 511 |
| Last Updated: | Sep 12, 2026 |
You use Azure Machine Learning Designer to load the following datasets into an experiment: Dataset1

You use Azure Machine Learning Designer to load the following datasets into an experiment: You need to create a dataset that has the same columns and header row as the input datasets and contains all rows from both input datasets. Solution: Use the Join Data component. Does the solution meet the goal?
You create an Azure Machine Learning pipeline named pipeline 1 with two steps that contain Python scnpts. Data processed by the first step is passed to the second step. You must update the content of the downstream data source of pipeline 1 and run the pipeline again. You need to ensure the new run of pipeline 1 fully processes the updated content. Solution: Change the value of the compute.target parameter of the PythonScriptStep object in the two steps. Does the solution meet the goal'
You plan to use the Hyperdrive feature of Azure Machine Learning to determine the optimal hyperparameter values when training a model. You must use Hyperdrive to try combinations of the following hyperparameter values: learning_rate: any value between 0.001 and 0.1 batch_size: 16, 32, or 64 You need to configure the search space for the Hyperdrive experiment. Which two parameter expressions should you use? Each correct answer presents part of the solution. NOTE: Each correct selection is worth one point.
You manage an Azure Machine Learning workspace. You plan to irain a natural language processing (NLP) tew classification model in multiple languages by using Azure Machine learning Python SDK v2. You need to configure the language of the text classification job by using automated machine learning. Which method of the TextClassifkationlob class should you use?
You use the following Python code in a notebook to deploy a model as a web service:

The deployment fails. You need to use the Python SDK in the notebook to determine the events that occurred during service deployment an initialization. Which code segment should you use?