AWS Certified Machine Learning Engineer – Associate (MLA-C01) Free Practice Exam Questions

198 real AWS Certified Machine Learning Engineer – Associate (MLA-C01) exam questions with answers and AI explanations. Amazon Web Services certification prep — page 5 of 20.

Question 41: An ML engineer needs to use data with Amazon SageMaker Canvas to train an ML model. The data is stored in Amazon S3 and is complex in structure. The ML enginee…
Question 42: An ML engineer is evaluating several ML models and must choose one model to use in production. The cost of false negative predictions by the models is much hig…
Question 43: A company is using an Amazon Redshift database as its single data source. Some of the data is sensitive. A data scientist needs to use some of the sensitive da…
Question 44: An ML engineer is using a training job to fine-tune a deep learning model in Amazon SageMaker Studio. The ML engineer previously used the same pre-trained mode…
Question 45: A credit card company has a fraud detection model in production on an Amazon SageMaker endpoint. The company develops a new version of the model. The company n…
Question 46: A company stores time-series data about user clicks in an Amazon S3 bucket. The raw data consists of millions of rows of user activity every day. ML engineers…
Question 47: A company has deployed an ML model that detects fraudulent credit card transactions in real time in a banking application. The model uses Amazon SageMaker Asyn…
Question 48: An ML engineer needs to implement a solution to host a trained ML model. The rate of requests to the model will be inconsistent throughout the day. The ML engi…
Question 49: A company uses Amazon SageMaker Studio to develop an ML model. The company has a single SageMaker Studio domain. An ML engineer needs to implement a solution t…
Question 50: A company uses Amazon SageMaker for its ML workloads. The company's ML engineer receives a 50 MB Apache Parquet data file to build a fraud detection model. The…