Qwissit Artificial Intelligence

AWS AIF-C01

ML Lifecycle and MLOps

12 of 60 questions in the app

ML pipeline

  1. Which order of phases is typical in an ML project? Easy
  2. What is the goal of exploratory data analysis (EDA)? Easy
  3. Which work belongs to data pre-processing? Easy
  4. What is meant by feature engineering? Easy
  5. What are hyperparameters? Easy
  6. What is a separate test dataset for? Easy

Model sources and operation

  1. What is an advantage of a pre-trained open-source model over training your own from scratch? Easy
  2. What does it mean to use a foundation model through a managed API such as Amazon Bedrock? Easy

ML pipeline

  1. Which activities belong to the phase before the actual training? Medium
  2. How does Amazon SageMaker AI support hyperparameter tuning? Medium

AWS services in the lifecycle

  1. Which mappings of pipeline phase and AWS tool are correct? Hard
  2. A team without its own ML specialists wants to predict cancellations from tabular data. A second team with data scientists wants to automate the workflow from data import to approval. Which mapping fits? Hard

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