DP-100 Exam Preparation Material | Designing and Implementing a Data Science Solution on Azure

Prepare for the DP-100 with reliable study materials, practice questions, and key exam insights.

Prepare for the DP-100 Designing and Implementing a Data Science Solution on Azure exam with CertQueen's independently developed study resources. Review important concepts, practice scenario-based questions, and use clear explanations to identify areas that require further study.

Question#1

DRAG DROP
You create an Azure Machine Learning workspace. You are training a classification model with no-code AutoML in Azure Machine Learning studio.
The model must predict if a client of a financial institution will subscribe to a fixed-term deposit. You must identify the feature that has the most influence on the predictions of the model for the second highest scoring algorithm. You must minimize the effort and time to identify the feature.
You need to complete the identification.
Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.


A. 

Question#2

DRAG DROP
You have an existing GitHub repository containing Azure Machine Learning project files.
You need to clone the repository to your Azure Machine Learning shared workspace file system.
Which four actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order. NOTE: More than one order of answer choices is correct. You will receive credit for any of the correct orders you select.


A. 

Question#3

You plan to run a Python script as an Azure Machine Learning experiment.
The script contains the following code:
import os, argparse, glob
from azureml.core import Run
parser = argparse.ArgumentParser()
parser.add_argument('--input-data',
type=str, dest='data_folder')
args = parser.parse_args()
data_path = args.data_folder
file_paths = glob.glob(data_path + "/*.jpg")
You must specify a file dataset as an input to the script. The dataset consists of multiple large image files and must be streamed directly from its source.
You need to write code to define a ScriptRunConfig object for the experiment and pass the ds dataset as an argument.
Which code segment should you use?

A. arguments = ['--input-data', ds.to_pandas_dataframe()]
B. arguments = ['--input-data', ds.as_mount()]
C. arguments = ['--data-data', ds]
D. arguments = ['--input-data', ds.as_download()]

Explanation:
If you have structured data not yet registered as a dataset, create a TabularDataset and use it directly in your training script for your local or remote experiment.
To load the TabularDataset to pandas DataFrame
df = dataset.to_pandas_dataframe()
Note: TabularDataset represents data in a tabular format created by parsing the provided file or list of files.
Reference: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-train-with-datasets

Question#4

You use Azure Machine Learning Designer lo load the following datasets into an experiment:
Dataset1:



Dataset2:



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 Add Rows component.
Does the solution meet the goal?

A. Yes
B. No

Question#5

You are a data scientist creating a linear regression model.
You need to determine how closely the data fits the regression line.
Which metric should you review?

A. Coefficient of determination
B. Recall
C. Precision
D. Mean absolute error
E. Root Mean Square Error

Explanation:
Coefficient of determination, often referred to as R2, represents the predictive power of the model as a value between 0 and 1. Zero means the model is random (explains nothing); 1 means there is a perfect fit. However, caution should be used in interpreting R2 values, as low values can be entirely normal and high values can be suspect.
Reference: https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/evaluate-model

Exam Code: DP-100
Q & A: 506 Q&As         Updated:  Sep 05,2025

 

 Access Complete DP-100 Preparation Material

What This DP-100 Study Resource Helps You Do

Review Key Concepts

Review the technologies, products, processes, and practical skills covered by the current DP-100 exam objectives.

Practice Scenario-Based Questions

Work through independently developed questions designed to strengthen your understanding of technical scenarios and decision-making.

Identify Knowledge Gaps

Use your results and the provided explanations to find weaker areas and focus your study more effectively.

How to Use This DP-100 Preparation Material

Review the Exam Scope

Start by reviewing the topics covered by the DP-100 exam. Compare them with the official exam objectives to understand the required technologies, operational tasks, and practical skills, then identify the areas that deserve the most attention.

Practice Independently

Complete a focused set of practice questions for each topic. On your first attempt, avoid referring to notes, answers, or other study resources so that you can evaluate your current understanding more accurately.

Study the Explanations

Review the answers and explanations after completing each practice session. Understand why the correct option is appropriate for the given scenario and why the other options may be incorrect or less suitable.

Close Knowledge Gaps

Keep track of incorrect answers, unfamiliar concepts, and weaker knowledge areas. Review these topics using official documentation and practical experience, then answer the related questions again to reinforce your understanding and monitor your progress.

Independent DP-100 Preparation Resource

CertQueen independently develops its certification study materials for educational purposes. The practice questions are not copied from, recalled from, or presented as live or official exam questions.

CertQueen is not affiliated with, endorsed by, sponsored by, or authorized by any certification provider. Certification names, exam codes, product names, and related trademarks are the property of their respective owners and are referenced only for identification and educational purposes.