Pre-Summer Special Sale - 70% Discount Offer - Ends in 0d 00h 00m 00s - Coupon code: best70

Page: 1 / 8
Total 80 questions
Exam Code: DP-100                Update: Apr 19, 2026
Exam Name: Designing and Implementing a Data Science Solution on Azure

Microsoft Designing and Implementing a Data Science Solution on Azure DP-100 Exam Dumps: Updated Questions & Answers (April 2026)

Question # 1

You have an Azure Machine Learning workspace named workspaces.

You must add a datastore that connects an Azure Blob storage container to workspaces. You must be able to configure a privilege level.

You need to configure authentication.

Which authentication method should you use?

A.

Account key

B.

SAS token

C.

Service principal

D.

Managed identity

Question # 2

You train classification and regression models by using automated machine learning.

You must evaluate automated machine learning experiment results. The results include how a classification model is making systematic errors in its predictions and the relationship between the target feature and the regression model ' s predictions. You must use charts generated by automated machine learning.

You need to choose a chart type for each model type.

Which chart types should you use? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

Question # 3

You manage an Azure Al Foundry project.

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

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

• Verifying the Al-generated responses align with and are validated by the provided context.

You need to identify an evaluation metric and a comparison feature to assess the performance of the model. 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 # 4

You create a deep learning model for image recognition on Azure Machine Learning service using GPU-based training.

You must deploy the model to a context that allows for real-time GPU-based inferencing.

You need to configure compute resources for model inferencing.

Which compute type should you use?

A.

Azure Container Instance

B.

Azure Kubernetes Service

C.

Field Programmable Gate Array

D.

Machine Learning Compute

Question # 5

You create an Azure Machine Learning compute resource to train models. The compute resource is configured as follows:

Minimum nodes: 2

Maximum nodes: 4

You must decrease the minimum number of nodes and increase the maximum number of nodes to the following values:

Minimum nodes: 0

Maximum nodes: 8

You need to reconfigure the compute resource.

What are three possible ways to achieve this goal? Each correct answer presents a complete solution.

NOTE: Each correct selection is worth one point.

A.

Azure Machine Learning designer

B.

Azure CLI ml extension v2

C.

Azure Machine Learning studio

D.

BuildContext class in Python SDK v2

E.

MLCIient class in Python SDK v2

Question # 6

You have an Azure Machine Learning workspace. You build a deep learning model.

You need to publish a GPU-enabled model as a web service.

Which two compute targets can you use? Each correct answer presents a complete solution.

NOTE: Each correct selection is worth one point.

A.

Azure Kubernetes Service (AKS)

B.

Azure Container Instances (ACI)

C.

Local web service

D.

Azure Machine Learning compute clusters

Question # 7

You are performing a classification task in Azure Machine Learning Studio.

You must prepare balanced testing and training samples based on a provided data set.

You need to split the data with a 0.75:0.25 ratio.

Which value should you use for each parameter? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

Question # 8

You train a classification model by using a decision tree algorithm.

You create an estimator by running the following Python code. The variable feature_names is a list of all feature names, and class_names is a list of all class names.

from interpret.ext.blackbox import TabularExplainer

You need to explain the predictions made by the model for all classes by determining the importance of all features.

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 # 9

You are using C-Support Vector classification to do a multi-class classification with an unbalanced training dataset. The C-Support Vector classification using Python code shown below:

You need to evaluate the C-Support Vector classification code.

Which evaluation statement should you use? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

Question # 10

You ate reviewing model benchmarks in Azure Al Foundry.

You must use an embedding model that can assess rank-order relevance based on cosine similarity. You need to select the applicable embedding model. Which model metric should you focus on?

A.

V measure

B.

Mean average precision

C.

F1 score

D.

Spearman correlation

Page: 1 / 8
Total 80 questions

Most Popular Certification Exams

Payment

       

Contact us

Site Secure

mcafee secure

TESTED 19 Apr 2026