AWS Certified Machine Learning - Specialty (MLS-C01) Exam - Demo File

Sep 20, 2026

Uploaded by Mimi

Practice exam material for AWS Certified Machine Learning – Specialty (MLS-C01), provided as a demo file. The content includes multiple-choice questions and answers covering core machine learning and AWS services concepts such as SageMaker training job parameters, metrics storage formats for query performance, feature encoding for categorical variables, handling overfitting and class-imbalance issues, data cleaning for incorrect numeric inputs, and choosing scalable data storage that supports SQL exploration. It also discusses model behavior degradation in production scenarios.

LanguageEnglish

CategoryExam

FormatPDF

Pages6

Reading Time15 min

AccessFree to download

Practice Questions

Training jobs and required parameters

Monitoring data storage for query performance

Encoding day-of-week to binary

Mitigating overfitting and dataset issues

Cleaning incorrect patient age values

Scalable training data storage with SQL

Production recommendation model degradation

Page No | 1 Amazon AWS-Certified-Machine-Learning-Specialty EXAM AWS Certified Machine Learning -Specialty (MLS-C01) Exam Product: Demo File For More Information: [https://www.dumpsplanet.com/AWS-Certified-Machine-Learning-Specialty-dumps](https://www.dumpsplanet.com/AWS-Certified-Machine-Learning-Specialty-dumps) [https://www.dumpsplanet.com](https://www.dumpsplanet.com) Page No | 2 Question: 1 When submitting Amazon Sage Maker training jobs using one of the built-in algorithms, which common parameters MUST be specified? (Choose three. ) A. The training channel identifying the location of training data on an Amazon S3 bucket. B. The validation channel identifying the location of validation data on an Amazon S3bucket. C. Iam role that Amazon Sage Maker can assume toper form task son behalf of the users. D. Hyper parameters in a JSON array as documented for the algorithm used. E. The Amazon EC2 instance class specifying whether training will be run using CPU or GPU. F. The output paths pacifying where on an Amazon S3 bucket the trained model will persist. Answer : A, E, F Question: 2 A monitoring service generates 1 TB of scale metrics record data every minute. A Research team performs queries on this data using Amazon A then a. The queries run slowly due to the large volume of data, and the team requires better performance. How should the records be stored in Amazon S3 to improve query performance? A. CSV files B. Parquet files C. Compressed JSON D. Record lO Answer: B Question: 3 Machine Learning Specialist is working with a media company to perform classification on popular articles from the company's website. The company is using random forests to classify how popular an article will be before it is published. A sample of the data being used is below. Page No | 3 Given the dataset, the Specialist wants to convert the Day_Of_Week column to binary values. What technique should be used to convert this column to binary values? A. Binarization B. One-hot encoding C. Tokenization D. Normalization transformation Answer: B Question: 4 A gaming company has launched an online game where people can start playing for free, but they need to pay if they choose to use certain features. The company needs to build an automated system to predict whether or not a new user will become a paid user within 1 year. The company has gathered a labeled dataset from 1 million users. The training dataset consists of 1,000 positive samples (from users who ended up paying within 1 year) and 999,000 negative samples (from users who did not use any paid features) . Each data sample consists of 200 features including user age, device, location, and play patterns. Using this dataset for training, the Data Science team trained a random forest model that converged with over99% accuracy onthe training set. However, the prediction resultson atestdataset were not satisfactory Which of the following approaches should the Data Science team take to mitigate this issue? (Choose two.) A. Add more deep trees to the random forest to enable the model to learn more features. B. Include a copy of the samples in the test dataset in the training dataset. C. Generate more positive samples by duplicating the positive samples and adding a small amount of noise to the duplicated data. D. Change the cost function so that false negatives have a higher impact on the cost value than false positives. E. Change the cost function so that false positives have a higher impact on the cost value than false negatives. Answer: B, D Question: 5 A Data Scientist is developing a machine learning model to predict future patient outcomes based on information collected about each patient and their treatment plans. The model should output a continuous value as its prediction. The data available includes labeled outcomes for a set of 4,000 patients. The study was conducted on a group of individuals over

FAQs

When submitting Amazon SageMaker training jobs with built-in algorithms, which parameters must be specified?

Specify the training channel for S3 training data, the IAM role SageMaker can assume, and the output path(s) where the trained model will be persisted in S3. (Correct options: A, E, F.)

How can 1 TB of minute-scale metrics records be stored to improve query performance?

Store the records in Parquet files. (Correct option: B.)

What technique should convert the Day_Of_Week column to binary values in the given dataset context?

Use one-hot encoding. (Correct option: B.)

Sep 20, 2026

Uploaded by Mimi