Cisco
CompTIA
ISC
EC-Council
EXIN
Fortinet
ITIL
Juniper
Microsoft
VMware
Avaya
SAP
Google
NVIDIA
Salesforce
Amazon
Palo Alto Networks
ISC2
Splunk
ServiceNow
All Vendors
  2. Home
  3. Exams
  4. Amazon
  5. AWS Certified Machine Learning - Specialty

Amazon AWS Certified Machine Learning - Specialty Exam
AWS Certified Machine Learning - Specialty (MLS-C01) (Page 5 )

Updated On: 1-Feb-2026
Page 5 of 68
PDF with 370 Questions

A data scientist has 20 TB of data in CSV format in an Amazon S3 bucket. The data scientist needs to convert the data to Apache Parquet format.

How can the data scientist convert the file format with the LEAST amount of effort?

  1. Use an AWS Glue crawler to convert the file format.
  2. Write a script to convert the file format. Run the script as an AWS Glue job.
  3. Write a script to convert the file format. Run the script on an Amazon EMR cluster.
  4. Write a script to convert the file format. Run the script in an Amazon SageMaker notebook.

Answer(s): B



A bank wants to use a machine learning (ML) model to predict if users will default on credit card payments. The training data consists of 30,000 labeled records and is evenly balanced between two categories. For the model, an ML specialist selects the Amazon SageMaker built-in XGBoost algorithm and configures a SageMaker automatic hyperparameter optimization job with the Bayesian method. The ML specialist uses the validation accuracy as the objective metric.

When the bank implements the solution with this model, the prediction accuracy is 75%. The bank has given the ML specialist 1 day to improve the model in production.

Which approach is the FASTEST way to improve the model's accuracy?

  1. Run a SageMaker incremental training based on the best candidate from the current model's tuning job. Monitor the same metric that was used as the objective metric in the previous tuning, and look for improvements.
  2. Set the Area Under the ROC Curve (AUC) as the objective metric for a new SageMaker automatic hyperparameter tuning job. Use the same maximum training jobs parameter that was used in the previous tuning job.
  3. Run a SageMaker warm start hyperparameter tuning job based on the current model’s tuning job. Use the same objective metric that was used in the previous tuning.
  4. Set the F1 score as the objective metric for a new SageMaker automatic hyperparameter tuning job. Double the maximum training jobs parameter that was used in the previous tuning job.

Answer(s): C



A company stores its documents in Amazon S3 with no predefined product categories. A data scientist needs to build a machine learning model to categorize the documents for all the company's products.

Which solution will meet these requirements with the MOST operational efficiency?

  1. Build a custom clustering model. Create a Dockerfile and build a Docker image. Register the Docker image in Amazon Elastic Container Registry (Amazon ECR). Use the custom image in Amazon SageMaker to generate a trained model.
  2. Tokenize the data and transform the data into tabular data. Train an Amazon SageMaker k-means model to generate the product categories.
  3. Train an Amazon SageMaker Neural Topic Model (NTM) model to generate the product categories.
  4. Train an Amazon SageMaker Blazing Text model to generate the product categories.

Answer(s): C



A retail company wants to use Amazon Forecast to predict daily stock levels of inventory. The cost of running out of items in stock is much higher for the company than the cost of having excess inventory. The company has millions of data samples for multiple years for thousands of items. The company’s purchasing department needs to predict demand for 30-day cycles for each item to ensure that restocking occurs.

A machine learning (ML) specialist wants to use item-related features such as "category," "brand," and "safety stock count." The ML specialist also wants to use a binary time series feature that has "promotion applied?" as its name. Future promotion information is available only for the next 5 days.

The ML specialist must choose an algorithm and an evaluation metric for a solution to produce prediction results that will maximize company profit.

Which solution will meet these requirements?

  1. Train a model by using the Autoregressive Integrated Moving Average (ARIMA) algorithm. Evaluate the model by using the Weighted Quantile Loss (wQL) metric at 0.75 (P75).
  2. Train a model by using the Autoregressive Integrated Moving Average (ARIMA) algorithm. Evaluate the model by using the Weighted Absolute Percentage Error (WAPE) metric.
  3. Train a model by using the Convolutional Neural Network - Quantile Regression (CNN-QR) algorithm. Evaluate the model by using the Weighted Quantile Loss (wQL) metric at 0.75 (P75).
  4. Train a model by using the Convolutional Neural Network - Quantile Regression (CNN-QR) algorithm. Evaluate the model by using the Weighted Absolute Percentage Error (WAPE) metric.

Answer(s): C



An online retail company wants to develop a natural language processing (NLP) model to improve customer service. A machine learning (ML) specialist is setting up distributed training of a Bidirectional Encoder Representations from Transformers (BERT) model on Amazon SageMaker. SageMaker will use eight compute instances for the distributed training.

The ML specialist wants to ensure the security of the data during the distributed training. The data is stored in an Amazon S3 bucket.

Which combination of steps should the ML specialist take to protect the data during the distributed training? (Choose three.)

  1. Run distributed training jobs in a private VPC. Enable inter-container traffic encryption.
  2. Run distributed training jobs across multiple VPCs. Enable VPC peering.
  3. Create an S3 VPC endpoint. Then configure network routes, endpoint policies, and S3 bucket policies.
  4. Grant read-only access to SageMaker resources by using an IAM role.
  5. Create a NAT gateway. Assign an Elastic IP address for the NAT gateway.
  6. Configure an inbound rule to allow traffic from a security group that is associated with the training instances.

Answer(s): A,C,D



Viewing page 5 of 68
Viewing questions 21 - 25 out of 370 questions



Post your Comments and Discuss Amazon AWS Certified Machine Learning - Specialty exam prep with other Community members:

Join the AWS Certified Machine Learning - Specialty Discussion