AWS Certified Machine Learning Engineer Associate Exam Questions & Answers

All 45 questions

1. Q1 A customer service company is looking to enhance its chatbot by providing real-time voice interaction with users. The bot needs to handle…
2. Q2 A financial services company uses an AWS Lambda function to monitor transaction fraud detection metrics from an ML model deployed in Amazon…
3. Q3 A machine learning engineer is responsible for deploying a model in Amazon SageMaker. After deployment, the engineer needs to monitor the model…
4. Q4 A machine learning team is using Amazon SageMaker Experiments to run multiple training jobs with different hyperparameter configurations and feature sets. They…
5. Q5 An ML engineer is using Amazon SageMaker Data Wrangler to preprocess data for a machine learning project. They need to import customer…
6. Q6 A manufacturing company is building an anomaly detection system to identify defective products in its production lines. The datasets include sensor logs…
7. Q7 A company is training a deep learning model with billions of parameters, which is too large to fit on a single machine.…
8. Q8 A pharmaceutical company is using machine learning to analyze clinical trial data. They need to ingest raw data from multiple sources, such…
9. Q9 You are responsible for deploying a machine learning model on AWS SageMaker for a real-time prediction application. The application requires low latency…
10. Q10 A financial services company is building an automated pipeline to update its fraud detection ML model every week using Amazon SageMaker Pipelines.…
11. Q11 Which of the following summarizes the differences between a token and an embedding in the context of generative AI?
12. Q12 You are training a machine learning model using PyTorch on Amazon SageMaker and want to ensure that the system resources, such as…
13. Q13 What is the main difference between identity-based policies and resource-based policies in AWS IAM?
14. Q14 A data analyst wants to extract meaningful insights from unstructured customer feedback stored in Amazon S3. The insights should include key entities…
15. Q15 A travel company is building a customer support application that provides automated responses to user queries. The application uses Amazon Q Business…
16. Q16 A telecommunications company receives real-time network performance data streams from thousands of devices across its infrastructure. The data streams consist of thousands…
17. Q17 A machine learning team is using SageMaker Model Registry to manage the lifecycle of their models. After training a new version of…
18. Q18 You are a Senior ML Engineer at a global logistics company that heavily relies on machine learning models for optimizing delivery routes,…
19. Q19 A media company wants to build an automated video transcription and translation pipeline. They need to transcribe speech from videos, translate the…
20. Q20 A data scientist needs to set up monitoring for a deployed machine learning model using Amazon SageMaker. They are primarily concerned with…
21. Q21 Which of the following best describes how Amazon SageMaker handles data parallelism during distributed training?
22. Q22 An organization is deploying a machine learning model to edge devices with limited computing resources. They want to optimize the model to…
23. Q23 A data scientist is building a fraud detection model using Amazon SageMaker. The dataset is highly imbalanced, with only 2% of the…
24. Q24 You are an ML engineer working for a logistics company that uses machine learning models to optimize delivery routes, predict maintenance needs,…
25. Q25 A machine learning engineer is training a deep learning model on SageMaker using TensorFlow. During training, the model's performance stops improving, and…
26. Q26 A retail company uses Amazon SageMaker to train machine learning models for product recommendation. The team stores raw customer behavior data, such…
27. Q27 A media analytics company processes raw video metadata stored in Amazon S3 buckets to generate insights on audience engagement. The company needs…
28. Q28 A machine learning engineer is setting up a Jupyter notebook environment to streamline an end-to-end machine learning workflow, including model training and…
29. Q29 You are a machine learning engineer working for a telecommunications company that needs to develop a predictive maintenance model. The goal is…
30. Q30 A travel agency has collected a large volume of customer feedback recordings from calls made to its customer support team after launching…
31. Q31 A financial services company deployed a machine learning model using Amazon SageMaker Asynchronous Inference in the past with successful performance. Now, the…
32. Q32 A healthcare company needs to ensure compliance with data privacy regulations like HIPAA and GDPR for their sensitive information stored in S3…
33. Q33 You are a data scientist at a healthcare company developing a machine learning model to analyze medical imaging data, such as X-rays…
34. Q34 A company’s data science team uses Amazon SageMaker notebook instances to develop machine learning models. The team frequently collaborates on projects that…
35. Q35 You are a machine learning engineer at a healthcare startup that uses an Amazon SageMaker endpoint to deliver real-time diagnostics based on…
36. Q36 You are a Data Scientist working for an e-commerce platform that uses a machine learning model to recommend products to customers. The…
37. Q37 A machine learning engineer is using Amazon SageMaker Studio to perform exploratory data analysis on a large dataset stored in Amazon S3.…
38. Q38 A company is using a fleet of Amazon EC2 instances to ingest data from on-premises data sources. The data is in JSON…
39. Q39 A company is developing an AI solution that needs to reduce both underfitting and overfitting to ensure a balanced model. Which combination…
40. Q40 A team is training a neural network model in Amazon SageMaker. During training, they notice that the model's performance has plateaued, and…
41. Q41 You are a data scientist working for an e-commerce company that wants to implement personalized product recommendations for its users. The company…
42. Q42 Which of the following types of drift is best described as a systematic favoring of certain groups in the model's predictions over…
43. Q43 An organization needs to develop and deploy a machine learning model for real-time customer behavior prediction using SageMaker. They want a solution…
44. Q44 You are evaluating the performance of a machine learning model and want to ensure that it generalizes well on unseen data. You…
45. Q45 What is the key challenge that results from a high variance model in the context of responsible AI, and what technique is…