AWS AIF-C01 DOMAIN 1 OF 5

AWS AIF-C01: Fundamentals of AI and ML

The provider lists this domain at 20% of the exam.

In plain English

The vocabulary of machine learning: what a model is, how it learns from data, how it is measured, and how it is used once it is trained.

What the provider lists under it

  • Basic AI concepts and terminology
  • Practical use cases for AI
  • The AI/ML development lifecycle
  • Types of inferencing
  • Types of learning: supervised, unsupervised, reinforcement
  • Model performance and business metrics

Terms worth knowing

  • Supervised vs unsupervised learning: Supervised learning trains on labelled examples. Unsupervised learning looks for structure in unlabelled data.
  • Overfitting: When a model learns its training data too closely and does badly on new data.
  • Model drift: A model getting worse over time because the real world no longer looks like its training data.

Quick answers

How much of the AWS AIF-C01 exam is Fundamentals of AI and ML?

The provider lists it at 20% of the exam, according to the AWS exam guide (version 1.2).

What topics are in Fundamentals of AI and ML?

Basic AI concepts and terminology; Practical use cases for AI; The AI/ML development lifecycle; Types of inferencing; Types of learning: supervised, unsupervised, reinforcement; Model performance and business metrics.

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Domain names, weights and topic lists come from the AWS exam guide (version 1.2), checked 2 November 2026. Providers change their outlines, so confirm the current version before you book. The plain-English explanations are ours, not the provider’s. Not affiliated with, endorsed by or sponsored by any certification vendor or exam body. Certification names, exam codes and product names are trademarks of their respective owners and are used only to identify the exam a practice product prepares for. Our questions are original and are not actual exam questions.