MLA-C01 Practice Questions
AWS Certified Machine Learning Engineer - Associate
Last Update 4 days ago
Total Questions : 241
Dive into our fully updated and stable MLA-C01 practice test platform, featuring all the latest AWS Certified Associate exam questions added this week. Our preparation tool is more than just a Amazon Web Services study aid; it's a strategic advantage.
Our free AWS Certified Associate practice questions crafted to reflect the domains and difficulty of the actual exam. The detailed rationales explain the 'why' behind each answer, reinforcing key concepts about MLA-C01. Use this test to pinpoint which areas you need to focus your study on.
A company has a large collection of chat recordings from customer interactions after a product release. An ML engineer needs to create an ML model to analyze the chat data. The ML engineer needs to determine the success of the product by reviewing customer sentiments about the product.
Which action should the ML engineer take to complete the evaluation in the LEAST amount of time?
A company ingests sales transaction data using Amazon Data Firehose into Amazon OpenSearch Service. The Firehose buffer interval is set to 60 seconds.
The company needs sub-second latency for a real-time OpenSearch dashboard.
Which architectural change will meet this requirement?
A company collects customer data daily and stores it as compressed files in an Amazon S3 bucket partitioned by date. Each month, analysts process the data, check data quality, and upload results to Amazon QuickSight dashboards.
An ML engineer needs to automatically check data quality before the data is sent to QuickSight, with the LEAST operational overhead.
Which solution will meet these requirements?
An ML engineer is collecting data to train a classification ML model by using Amazon SageMaker AI. The target column can have two possible values: Class A or Class
B.
The ML engineer wants to ensure that the number of samples for both Class A and Class B are balanced, without losing any existing training data. The ML engineer must test the balance of the training data.Which solution will meet this requirement?
A company has an ML model that needs to run one time each night to predict stock values. The model input is 3 MB of data that is collected during the current day. The model produces the predictions for the next day. The prediction process takes less than 1 minute to finish running.
How should the company deploy the model on Amazon SageMaker to meet these requirements?
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 that provides an automated alert when SageMaker AI compute costs reach a specific threshold.
Which solution will meet these requirements?
An ML engineer normalized training data by using min-max normalization in AWS Glue DataBrew. The ML engineer must normalize production inference data in the same way before passing the data to the model.
Which solution will meet this requirement?
Case study
An ML engineer is developing a fraud detection model on AWS. The training dataset includes transaction logs, customer profiles, and tables from an on-premises MySQL database. The transaction logs and customer profiles are stored in Amazon S3.
The dataset has a class imbalance that affects the learning of the model ' s algorithm. Additionally, many of the features have interdependencies. The algorithm is not capturing all the desired underlying patterns in the data.
The training dataset includes categorical data and numerical data. The ML engineer must prepare the training dataset to maximize the accuracy of the model.
Which action will meet this requirement with the LEAST operational overhead?
A company has developed a computer vision model. The company needs to deploy the model into production on Amazon SageMaker AI. The company has not hosted a model on SageMaker AI previously.
An ML engineer needs to implement a solution to track model versions. The solution also must provide recommendations about which Amazon EC2 instance types to use to host the model.
Which solution will meet these requirements?
A logistics company has installed in-vehicle cameras for basic monitoring of its drivers. The company wants to improve driver safety by identifying distractions that could lead to accidents.
Which solution will meet this requirement with the LEAST operational effort?
