AWSCertified AI Practitioner
Domain 1Objective 3
Task Statement 1.3: Describe the AI/ML Development Lifecycle. AIF-C01 Practice Questions (Page 4)
Part of the Content Domain 1: Fundamentals of AI and ML domain, which makes up ~20% of our current practice bank. AWS does not publish an official question count, but from its 90-minute exam (~35–60 total, ~7–12 in this domain), expect 2–4 from this objective — we provide 29 practice questions to prepare you well beyond it. (estimate)
29questions here
6free pages
7concepts
Questions 16–20
- 16
Which model performance metric measures the proportion of true positive predictions out of all actual positive instances in the dataset?
Select an answer first - 17
Which MLOps practice involves continuously observing a deployed model's performance to detect issues such as data drift or model degradation?
Select an answer first - 18
A data science team is building a binary classification model to predict customer churn. They have historical data with labeled outcomes. After splitting the data into training and test sets, they train several models and evaluate them on the test set. The team wants to identify the model that minimizes the number of false negatives, because failing to identify a churning customer is more costly than a false alarm. Which metric should they primarily use to select the model?
Select an answer first - 19
Which stage of an AI/ML pipeline involves cleaning raw data, handling missing values, and transforming features into a format suitable for model training?
Select an answer first - 20
A company wants to build a custom ML model using their own data. They need a fully managed service that can handle the entire training and deployment workflow, including experiment tracking and model hosting. Which AWS service should they use?
Select an answer first
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