AWS Certified AI Practitioner Vocabulary Game
Exam terms with clues and explanations by OpenExamPrep.
About the AWS Certified AI Practitioner Vocabulary Games
4 free word games built on 40 AWS Certified AI Practitioner terms across 5 topics. Every game deals terms at random and shows what each term means, so you can keep playing as long as you like.
How to Play
- 1.Read the clue and type the term (3 to 6 letters).
- 2.Green: right spot. Yellow: wrong spot. Gray: not in the term.
- 3.Solve it in 6 tries, then read the explanation.
- 1.Swap two neighboring tiles to line up 3 of the same term.
- 2.Longer lines, two lines at once and chains score more.
- 3.Play until no swap can make a line.
- 1.Flip two cards. A matching pair stays face up.
- 2.Each pair you find shows what the term means.
- 3.Clear the board in as few moves as you can.
- 1.Find each listed term in the letter grid.
- 2.Drag across its letters: across, down or diagonally.
- 3.Find all five as fast as you can.
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Topics in the AWS Certified AI Practitioner Vocabulary Game
AI and ML fundamentals
Generative AI fundamentals
Foundation model applications
Responsible AI guidelines
AI security and governance
Sources for these terms (39)
- AWS Certified AI Practitioner (AIF-C01) Exam Guide (Version 1.4) · Source checked 2026-11-01
- What is Amazon Comprehend? — Amazon Comprehend Developer Guide · Source checked 2026-11-01
- What Is Amazon Polly? — Amazon Polly Developer Guide · Source checked 2026-11-01
- What is Amazon Lex V2? — Amazon Lex V2 Developer Guide · Source checked 2026-11-01
- Batch transform for inference with Amazon SageMaker AI — Amazon SageMaker Developer Guide · Source checked 2026-11-01
- Process multiple prompts with batch inference — Amazon Bedrock User Guide · Source checked 2026-11-01
- Metrics and validation — Amazon SageMaker Developer Guide · Source checked 2026-11-01
- Binary Model Insights — Amazon Machine Learning Developer Guide · Source checked 2026-11-01
- Review metrics for an automated model evaluation job in Amazon Bedrock — Amazon Bedrock User Guide · Source checked 2026-11-01
- Customize your model to improve its performance for your use case — Amazon Bedrock User Guide · Source checked 2026-11-01
- Custom model hyperparameters — Amazon Bedrock User Guide · Source checked 2026-11-01
- Create, store, and share features with Feature Store — Amazon SageMaker Developer Guide · Source checked 2026-11-01
- Prompt engineering concepts — Amazon Bedrock User Guide · Source checked 2026-11-01
- What is prompt engineering? — Amazon Bedrock User Guide · Source checked 2026-11-01
- Influence response generation with inference parameters — Amazon Bedrock User Guide · Source checked 2026-11-01
- How Amazon Bedrock knowledge bases work — Amazon Bedrock User Guide · Source checked 2026-11-01
- What is Amazon Kendra? — Amazon Kendra Developer Guide · Source checked 2026-11-01
- Customize a model with fine-tuning in Amazon Bedrock — Amazon Bedrock User Guide · Source checked 2026-11-01
- Inference request parameters and response fields for foundation models — Amazon Bedrock User Guide · Source checked 2026-11-01
- Data and model quality monitoring with Amazon SageMaker Model Monitor — Amazon SageMaker Developer Guide · Source checked 2026-11-01
- Detecting drift in production applications — AWS Prescriptive Guidance · Source checked 2026-11-01
- SageMaker JumpStart pretrained models — Amazon SageMaker Developer Guide · Source checked 2026-11-01
- Understand options for evaluating large language models with SageMaker Clarify — Amazon SageMaker Developer Guide · Source checked 2026-11-01
- Understand the results of your model evaluation job — Amazon SageMaker Developer Guide · Source checked 2026-11-01
- Retrieve data and generate AI responses with Amazon Bedrock Knowledge Bases — Amazon Bedrock User Guide · Source checked 2026-11-01
- Automate tasks in your application using AI agents — Amazon Bedrock User Guide · Source checked 2026-11-01
- Using prompt datasets and available evaluation dimensions in model evaluation jobs — Amazon SageMaker Developer Guide · Source checked 2026-11-01
- Evaluate the performance of Amazon Bedrock resources — Amazon Bedrock User Guide · Source checked 2026-11-01
- Model Explainability with Amazon SageMaker Clarify — Amazon SageMaker Developer Guide · Source checked 2026-11-01
- Amazon SageMaker Model Cards — Amazon SageMaker Developer Guide · Source checked 2026-11-01
- Detect and filter harmful content by using Amazon Bedrock Guardrails — Amazon Bedrock User Guide · Source checked 2026-11-01
- What is IAM? — AWS Identity and Access Management User Guide · Source checked 2026-11-01
- What is Amazon Macie? — Amazon Macie User Guide · Source checked 2026-11-01
- AWS Key Management Service — AWS KMS Developer Guide · Source checked 2026-11-01
- What Is AWS Config? — AWS Config Developer Guide · Source checked 2026-11-01
- What is AWS Audit Manager? — AWS Audit Manager User Guide · Source checked 2026-11-01
- What is AWS Artifact? — AWS Artifact User Guide · Source checked 2026-11-01
- Overview of Amazon Titan models - Amazon Bedrock · Source checked 2026-11-02
- AWS Audit Manager availability change · Source checked 2026-11-02
About the AWS AI Practitioner Exam
The AWS Certified AI Practitioner (AIF-C01) validates foundational understanding of AI, machine learning, generative AI, AWS AI tools, responsible AI, and security/governance concepts for candidates who use but do not necessarily build AI/ML solutions on AWS.
Exam sponsor: Amazon Web Services (AWS) / Pearson VUE. The requirements and fees below concern the certification or admission exam, separate from our free practice resources.
Assessment
65 total questions: 50 scored and 15 unscored; multiple choice, multiple response, ordering, and matching question types.
Time Limit
90 minutes
Passing Score
700 scaled score on a 100-1000 scale
Exam / Certification Fees
$100 USD plus applicable taxes or foreign exchange adjustments
Exam sponsor websiteReported exam pass rate: Not published by AWS. AWS's certification FAQ and the AIF-C01 exam page publish no pass rate (checked 2026-10-22). Exam sponsor website
Fees, eligibility, and exam policies can change. Confirm them with the exam sponsor before applying or paying.
Frequently Asked Questions
Is the AWS AIF-C01 vocabulary game free?
Yes. The game is free to play with no sign-up. Signing in adds AI explanations for any term.
How do the AWS AIF-C01 vocabulary games work?
There are 4 games built on 40 AWS AIF-C01 terms. In Guess the Term, a clue describes one term and you have six tries to spell it, with green, yellow and gray letters showing how close you are. In Term Match, six terms appear as colored tiles; swap neighbors to line up three or more of the same term, and each match shows what the term means. In Term Pairs, twelve face-down cards hide six pairs of terms; flip two at a time to find each pair, and every pair you find shows what the term means. In Term Search, five terms hide in a grid of letters, reading across, down or diagonally; drag across a term to circle it, and each term you find shows what it means.
Where do the AWS AIF-C01 terms come from?
OpenExamPrep researched each term from the Amazon Web Services (AWS) / Pearson VUE content outline and primary sources, listed under Sources on this page. The game is independent study material, not an official exam resource.
What is AWS Certified AI Practitioner?
AWS Certified AI Practitioner (AIF-C01) is a foundational AWS certification for people who want to demonstrate AI, machine learning, generative AI, AWS AI tools, responsible AI, and governance literacy without needing to build or tune ML models.
How many questions are on the AWS AI Practitioner exam?
AWS lists 65 total questions on the certification overview. The exam guide explains that 50 questions affect your score and 15 unscored questions are mixed in and not identified.