Microsoft DP-100 Online Practice Questions and Exam Preparation

Microsoft DP-100 Online Questions & Answers

• Question 371:

  You are developing a two-step Azure Machine Learning pipeline by using the Azure Machine Learning SDK for Python.

  You need to register the output of the pipeline as a new version of a named dataset after the run has been completed.

  What should you implement?

  A. the as_input method of the OutputDatasetConfig class
  B. the register_on_complete method of the OutputDatasetConfig class
  C. the as_mount method of the DatasetConsumptionConfig class
  D. the as_download method of the DatasetConsumptionConfig class
  B. the register_on_complete method of the OutputDatasetConfig class

  ---

  Explanation

  https://learn.microsoft.com/en-us/python/api/azureml-core/azureml.data.output_dataset_config.outputdatasetconfig

  https://learn.microsoft.com/en-us/python/api/azureml-core/azureml.data.dataset_consumption_config.datasetconsumptionconfig

• Question 372:

  HOTSPOT

  You have a multi-class image classification deep learning model that uses a set of labeled photographs. You create the following code to select hyperparameter values when training the model.

  

  For each of the following statements, select Yes if the statement is true. Otherwise, select No.

  NOTE: Each correct selection is worth one point.

  

  

  ---

  Box 1: Yes

  Hyperparameters are adjustable parameters you choose to train a model that govern the training process itself. Azure Machine Learning allows you to automate hyperparameter exploration in an efficient manner, saving you significant time and resources. You specify the range of hyperparameter values and a maximum number of training runs. The system then automatically launches multiple simultaneous runs with different parameter configurations and finds the configuration that results in the best performance, measured by the metric you choose. Poorly performing training runs are automatically early terminated, reducing wastage of compute resources. These resources are instead used to explore other hyperparameter configurations.

  Box 2: Yes

  uniform(low, high) - Returns a value uniformly distributed between low and high

  Box 3: No

  Bayesian sampling does not currently support any early termination policy.

  https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters

• Question 373:

  You are moving a large dataset from Azure Machine Learning Studio to a Weka environment.

  You need to format the data for the Weka environment.

  Which module should you use?

  A. Convert to CSV
  B. Convert to Dataset
  C. Convert to ARFF
  D. Convert to SVMLight
  C. Convert to ARFF

  ---

  Explanation

  Use the Convert to ARFF module in Azure Machine Learning Studio, to convert datasets and results in Azure Machine Learning to the attribute-relation file format used by the Weka toolset. This format is known as ARFF.

  The ARFF data specification for Weka supports multiple machine learning tasks, including data preprocessing, classification, and feature selection. In this format, data is organized by entites and their attributes, and is contained in a single text file.

  References:

  https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/convert-to-arff

• Question 374:

  HOTSPOT

  You manage an Azure AI Foundry project.

  You plan to evaluate a fine-tuned large language model by performing the following tasks:

  1. Identifying discrepancies between runs of the same model to pinpoint areas where adjustments may be needed

  2. Verifying that AI-generated responses align with and are validated by the provided context

  You need to identify an evaluation metric and a comparison feature to assess model performance.

  Which assessment techniques should you use? To answer, select the appropriate options in the answer area.

  NOTE: Each correct selection is worth one point.

  

  

• Question 375:

  You are in the process of carrying out feature engineering on a dataset.

  You want to add a feature to the dataset and fill the column value.

  Recommendation: You must make use of the Join Data Azure Machine Learning Studio module.

  Will the requirements be satisfied?

  A. Yes
  B. No
  B. No

• Question 376:

  You manage an Azure Machine Learning workspace. The development environment for managing the workspace is configured to use Python SDK v2 in Azure Machine Learning Notebooks

  A Synapse Spark Compute is currently attached and uses system-assigned identity

  You need to use Python code to update the Synapse Spark Compute to use a user- assigned identity.

  Solution: Create an instance of the MLClient class.

  Does the solution meet the goal?

  A. Yes
  B. No
  B. No

• Question 377:

  DRAG DROP

  You have an Azure AI Foundry project named Projects.

  You are developing a web classification Prompt flow named Flow1 in Project1.

  The current input of Flow1 is defined as follows.

  

  You plan to add a large language model (LLM) node named Node1 to Flow1. Node1 will use an input named url of type string to classify the URL provided as Flow1 input.

  In Node1, you will add Jinja code to reference the value of its url input.

  You need to ensure Node1 classifies the provided URL values as the Flow1 input.

  How should you configure Node1? To answer, move the appropriate values to the correct Node1 configurations. You may use each value once, more than once, or not at all. You may need to move the split bar between panes or scroll to view content.

  Select and Place:

  

  

• Question 378:

  Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.

  After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.

  You create a model to forecast weather conditions based on historical data.

  You need to create a pipeline that runs a processing script to load data from a datastore and pass the processed data to a machine learning model training script.

  Solution: Run the following code:

  

  Does the solution meet the goal?

  A. Yes
  B. No
  B. No

  ---

  Explanation

  train_step is missing.

  https://docs.microsoft.com/en-us/python/api/azureml-pipeline-core/azureml.pipeline.core.pipelinedata?view=azure-ml-py

• Question 379:

  HOTSPOT

  You are using hyperparameter tuning in Azure Machine Learning Python SDK v2 to train a model.

  You configure the hyperparameter tuning experiment by running the following code:

  

  For each of the following statements, select Yes if the statement is true. Otherwise, select No.

  NOTE: Each correct selection is worth one point.

  

  

• Question 380:

  You plan to create a compute instance as part of an Azure Machine Learning development workspace.

  You must interactively debug code running on the compute instance by using Visual Studio Code Remote.

  You need to provision the compute instance.

  What should you do?

  A. Enable Remote Desktop Protocol (RDP) access.
  B. Modify role-based access control (RBAC) settings at the workspace level.
  C. Enable Secure Shell Protocol (SSH) access.
  D. Modify role-based access control (RBAC) settings at the compute instance level.
  C. Enable Secure Shell Protocol (SSH) access.