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Amazon Web Services MLS-C01 Exam With Confidence Using Practice Dumps

Exam Code:
MLS-C01
Exam Name:
AWS Certified Machine Learning - Specialty
Certification:
AWS Certified Specialty
Vendor:
Amazon Web Services
Questions:
330
Last Updated:
Apr 15, 2026
Exam Status:
Stable
Amazon Web Services MLS-C01

MLS-C01: AWS Certified Specialty Exam 2025 Study Guide Pdf and Test Engine

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AWS Certified Machine Learning - Specialty Questions and Answers

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Question 1

A Machine Learning Specialist receives customer data for an online shopping website. The data includes demographics, past visits, and locality information. The Specialist must develop a machine learning approach to identify the customer shopping patterns, preferences and trends to enhance the website for better service and smart recommendations.

Which solution should the Specialist recommend?

Options:

A.

Latent Dirichlet Allocation (LDA) for the given collection of discrete data to identify patterns in the customer database.

B.

A neural network with a minimum of three layers and random initial weights to identify patterns in the customer database

C.

Collaborative filtering based on user interactions and correlations to identify patterns in the customer database

D.

Random Cut Forest (RCF) over random subsamples to identify patterns in the customer database

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Question 2

A company uses sensors on devices such as motor engines and factory machines to measure parameters, temperature and pressure. The company wants to use the sensor data to predict equipment malfunctions and reduce services outages.

The Machine learning (ML) specialist needs to gather the sensors data to train a model to predict device malfunctions The ML spoctafst must ensure that the data does not contain outliers before training the ..el.

What can the ML specialist meet these requirements with the LEAST operational overhead?

Options:

A.

Load the data into an Amazon SagcMaker Studio notebook. Calculate the first and third quartile Use a SageMaker Data Wrangler data (low to remove only values that are outside of those quartiles.

B.

Use an Amazon SageMaker Data Wrangler bias report to find outliers in the dataset Use a Data Wrangler data flow to remove outliers based on the bias report.

C.

Use an Amazon SageMaker Data Wrangler anomaly detection visualization to find outliers in the dataset. Add a transformation to a Data Wrangler data flow to remove outliers.

D.

Use Amazon Lookout for Equipment to find and remove outliers from the dataset.

Question 3

A retail company is selling products through a global online marketplace. The company wants to use machine learning (ML) to analyze customer feedback and identify specific areas for improvement. A developer has built a tool that collects customer reviews from the online marketplace and stores them in an Amazon S3 bucket. This process yields a dataset of 40 reviews. A data scientist building the ML models must identify additional sources of data to increase the size of the dataset.

Which data sources should the data scientist use to augment the dataset of reviews? (Choose three.)

Options:

A.

Emails exchanged by customers and the company’s customer service agents

B.

Social media posts containing the name of the company or its products

C.

A publicly available collection of news articles

D.

A publicly available collection of customer reviews

E.

Product sales revenue figures for the company

F.

Instruction manuals for the company’s products

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