Amazon MLA-C01 Online Practice Questions and Exam Preparation

Amazon MLA-C01 Online Questions & Answers

• Question 1:

  HOTSPOT

  A company needs to train an ML model using historical transaction data to predict customer behavior. Choose the appropriate AWS service for each task related to handling this data. Each service should be selected only once or not at all.

  Tasks and corresponding AWS services:

  1. Store historical transaction data: Amazon S3

  2. Extract, transform, and load (ETL) data for training: AWS Glue

  3. Run SQL queries on the data for analysis: Amazon Athena

  

  

• Question 2:

  HOTSPOT

  An ML engineer is working on an ML model to predict the prices of similarly sized homes. The model will base predictions on several features The ML engineer will use the following feature engineering techniques to estimate the prices of the homes:

  1. Feature splitting

  2. Logarithmic transformation

  3. One-hot encoding

  4. Standardized distribution

  Select the correct feature engineering techniques for the following list of features. Each feature engineering technique should be selected one time or not at all (Select three.)

  

  

• Question 3:

  HOTSPOT

  An ML engineer is building a generative AI application on Amazon Bedrock by using large language models (LLMs). Select the correct generative AI term from the following list for each description. Each term should be selected one time or not at all. (Select three.)

  1. Embedding

  2. Retrieval Augmented Generation (RAG)

  3. Temperature

  4. Token

  

  

• Question 4:

  Which algorithm is most suitable for a use case that requires clustering unstructured text data?

  A. K-Means
  B. XGBoost
  C. Linear Regression
  D. Random Forest
  A. K-Means

• Question 5:

  Which metric is most appropriate for evaluating a binary classification model with imbalanced classes?

  A. Accuracy
  B. Precision-Recall AUC
  C. Mean Squared Error (MSE)
  D. R-squared
  B. Precision-Recall AUC

• Question 6:

  In Amazon SageMaker, which of the following is a managed capability for hyperparameter tuning?

  A. Batch transform
  B. AutoPilot
  C. Ground Truth
  D. Hyperparameter Tuning Jobs
  D. Hyperparameter Tuning Jobs

• Question 7:

  A model’s precision is 0.8 and recall is 0.6. What is the F1 score?

  A. 0.68
  B. 0.72
  C. 0.75
  D. 0.70
  B. 0.72

• Question 8:

  Which AWS service can help label large datasets efficiently using active learning and human annotators?

  A. Amazon Rekognition
  B. AWS Lambda
  C. Amazon SageMaker Ground Truth
  D. Amazon Comprehend
  C. Amazon SageMaker Ground Truth

• Question 9:

  You need to preprocess data by normalizing and scaling numerical features in Amazon SageMaker. Which tool should you use?

  A. Feature Store
  B. Data Wrangler
  C. SageMaker Neo
  D. SageMaker Ground Truth
  B. Data Wrangler

• Question 10:

  Which type of machine learning algorithm is best suited for detecting anomalies in network traffic?

  A. Supervised learning
  B. Unsupervised learning
  C. Reinforcement learning
  D. Semi-supervised learning
  B. Unsupervised learning