[May 19, 2026] Free CompTIA DY0-001 Exam Questions & Answer [Q46-Q61]

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[May 19, 2026] Free CompTIA DY0-001 Exam Questions and Answer

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CompTIA DY0-001 Exam Syllabus Topics:

Topic	Details
Topic 1	Operations and Processes: This section of the exam measures skills of an AI ML Operations Specialist and evaluates understanding of data ingestion methods, pipeline orchestration, data cleaning, and version control in the data science workflow. Candidates are expected to understand infrastructure needs for various data types and formats, manage clean code practices, and follow documentation standards. The section also explores DevOps and MLOps concepts, including continuous deployment, model performance monitoring, and deployment across environments like cloud, containers, and edge systems.
Topic 2	Specialized Applications of Data Science: This section of the exam measures skills of a Senior Data Analyst and introduces advanced topics like constrained optimization, reinforcement learning, and edge computing. It covers natural language processing fundamentals such as text tokenization, embeddings, sentiment analysis, and LLMs. Candidates also explore computer vision tasks like object detection and segmentation, and are assessed on their understanding of graph theory, anomaly detection, heuristics, and multimodal machine learning, showing how data science extends across multiple domains and applications.
Topic 3	Modeling, Analysis, and Outcomes: This section of the exam measures skills of a Data Science Consultant and focuses on exploratory data analysis, feature identification, and visualization techniques to interpret object behavior and relationships. It explores data quality issues, data enrichment practices like feature engineering and transformation, and model design processes including iterations and performance assessments. Candidates are also evaluated on their ability to justify model selections through experiment outcomes and communicate insights effectively to diverse business audiences using appropriate visualization tools.
Topic 4	Mathematics and Statistics: This section of the exam measures skills of a Data Scientist and covers the application of various statistical techniques used in data science, such as hypothesis testing, regression metrics, and probability functions. It also evaluates understanding of statistical distributions, types of data missingness, and probability models. Candidates are expected to understand essential linear algebra and calculus concepts relevant to data manipulation and analysis, as well as compare time-based models like ARIMA and longitudinal studies used for forecasting and causal inference.
Topic 5	Machine Learning: This section of the exam measures skills of a Machine Learning Engineer and covers foundational ML concepts such as overfitting, feature selection, and ensemble models. It includes supervised learning algorithms, tree-based methods, and regression techniques. The domain introduces deep learning frameworks and architectures like CNNs, RNNs, and transformers, along with optimization methods. It also addresses unsupervised learning, dimensionality reduction, and clustering models, helping candidates understand the wide range of ML applications and techniques used in modern analytics.

NEW QUESTION 46
A movie production company would like to find the actors appearing in its top movies using data from the tables below. The resulting data must show all movies in Table 1, enriched with actors listed in Table 2.

Which of the following query operations achieves the desired data set?

Perform an INNER JOIN between Table 1 using column Movie, and Table 2 using column Acted_In.

Perform a UNION between Table 1 using column Movie, and Table 2 using column Acted_In.

Perform an INTERSECT between Table 1 using column Movie, and Table 2 using column Acted_In.

Perform a LEFT JOIN on Table 1 using column Movie, with Table 2 using column Acted_In.

NEW QUESTION 47
An analyst wants to show how the component pieces of a company’s business units contribute to the company’s overall revenue. Which of the following should the analyst use to best demonstrate this breakdown?

Box-and-whisker chart

Sankey diagram

Scatter plot matrix

Residual chart

NEW QUESTION 48
Which of the following is the naive assumption in Bayes’ rule?

Normal distribution

Independence

Uniform distribution

Homoskedasticity

NEW QUESTION 49
Which of the following distribution methods or models can most effectively represent the actual arrival times of a bus that runs on an hourly schedule?

Binomial

Exponential

Normal

Poisson

NEW QUESTION 50
A data scientist wants to digitize historical hard copies of documents. Which of the following is the best method for this task?

Word2vec

Optical character recognition

Latent semantic analysis

Semantic segmentation

NEW QUESTION 51
A data scientist has built a model that provides the likelihood of an error occurring in a factory. The historical accuracy of the model is 90%. At a specific factory, the model is reporting a likelihood score of 0.90. Which of the following explains a confidence score of 0.90?

Running this model for all known factory issues, it is expected the model will identify 90 out of 100 known factory issues.

Running this model on 100 samples of factories, a certain model performance is expected for 90 out of the 100 samples.

Running this model 100 times on a factory, it is expected the model will predict 90 out of 100 factory errors.

Running this model 100 times within a factory it is expected the model will predict error 90 out of 100times the model is ran.

NEW QUESTION 52
Which of the following distance metrics for KNN is best described as a straight line?

Radial

Euclidean

Cosine

Manhattan

NEW QUESTION 53
A data scientist needs to analyze a company’s chemical businesses and is using the master database of the conglomerate company. Nothing in the data differentiates the data observations for the different businesses.
Which of the following is the most efficient way to identify the chemical businesses’ observations?

Ingest the data from all of the hard drives and perform exploratory data analysis to identify which business is responsible for chemical operations.

Perform analysis on all of the data and create a summary report on the results relevant to chemical operations.

Consult with the business team to identify which sites are responsible for chemical operations and ingest only the relevant data for analysis.

Ingest data from the hard drive containing the most data and present sample results on the chemicaloperations.

NEW QUESTION 54
Which of the following problem-solving approaches is a set of guidelines to handle highly variable and not fully apparent situations?

Schedule

Plan

Heuristic

Algorithm

NEW QUESTION 55
A data scientist is merging two tables. Table 1 contains employee IDs and roles. Table 2 contains employee IDs and team assignments. Which of the following is the best technique to combine these data sets?

inner join between Table 1 and Table 2

left join on Table 1 with Table 2

right join on Table 1 with Table 2

outer join between Table 1 and Table 2

NEW QUESTION 56
Which of the following environmental changes is most likely to resolve a memory constraint error when running a complex model using distributed computing?

Converting an on-premises deployment to a containerized deployment

Migrating to a cloud deployment

Moving model processing to an edge deployment

Adding nodes to a cluster deployment

NEW QUESTION 57
Which of the following methods should a data scientist use just before switching to a potential replacement model?

A/B testing

Performance monitoring

CI/CD

Containerization

NEW QUESTION 58
A computer vision model is trained to identify cats on a training set that is composed of both cat and dog images. The model predicts a picture of a cat is a dog. Which of the following describes this error?

Error due to reality

False positive error

Sampling error

Type II error

NEW QUESTION 59
Which of the following explains back propagation?

The passage of convolutions backward through a neural network to update weights and biases

The passage of accuracy backward through a neural network to update weights and biases

The passage of nodes backward through a neural network to update weights and biases

The passage of errors backward through a neural network to update weights and biases

NEW QUESTION 60
Which of the following measures would a data scientist most likely use to calculate the similarity of two text strings?

Word cloud

Edit distance

String indexing

k-nearest neighbors

NEW QUESTION 61
The following graphic shows the results of an unsupervised, machine-learning clustering model:

k is the number of clusters, and n is the processing time required to run the model. Which of the following is the best value of k to optimize both accuracy and processing requirements?

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CompTIA DY0-001 Exam Syllabus Topics:

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