AWS AIF-C01 Practice Test: Certified AI Practitioner

Last revised: June 29, 2026

Practice AWS Certified AI Practitioner (AWS AIF-C01) in IT Mastery with focused sample pages, topic drills, timed mock exams, detailed explanations, and the current question bank.

Use IT Mastery for interactive practice with timed mocks, topic drills, progress tracking, and detailed explanations across web and mobile. Focused topic pages and the static diagnostic page preview how this exam handles AI foundations, generative AI, AWS service selection, responsible-AI controls, and governance scenarios.

Practice preview and focused pages

Use this page to start the web app and choose the right public preview before longer mixed practice. For sample exam questions, use the focused topic pages, quick review, and free-practice page in this exam section; the interactive app remains the primary practice path.

  • Focused topic pages: drill focused topics including Applications of Foundation Models; Fundamentals of AI and ML; and other domains with explanations.
  • Quick review: High-yield AI, ML, generative AI, AWS service selection, security, evaluation, and practice focus.
  • Free practice exam: Try 65 free AWS Certified AI Practitioner (AWS AIF-C01) questions across the exam domains, with explanations, then continue with IT Mastery practice.

What this AIF-C01 practice page gives you

  • a direct web entry for AIF-C01 practice in IT Mastery
  • topic drills and mixed sets across AI/ML fundamentals, generative AI, responsible AI, and governance
  • detailed explanations that show why the best AWS AI answer is correct
  • a clear web preview path for previewing question style before deeper practice
  • the same IT Mastery account across web and mobile

AIF-C01 exam snapshot

  • Vendor: AWS
  • Official exam name: AWS Certified AI Practitioner (AIF-C01)
  • Exam code: AIF-C01
  • Items: 65 total, including 50 scored and 15 unscored
  • Exam time: 90 minutes
  • Question types: multiple choice, multiple response, ordering, and matching
  • Passing score: 700 scaled

AIF-C01 questions usually reward the option that applies the right AWS AI service, understands generative AI limits, and protects responsible-AI and governance expectations without overengineering the solution.

Topic coverage for AIF-C01 practice

DomainWeight
Fundamentals of AI and ML20%
Fundamentals of Generative AI24%
Applications of Foundation Models28%
Guidelines for Responsible AI14%
Security, Compliance, and Governance for AI Solutions14%

AIF-C01 AI decision filters

Use these filters when two AWS AI answers sound reasonable:

  • Use case before service: identify whether the task is prediction, classification, transcription, translation, document extraction, search, summarization, generation, or agentic workflow automation.
  • GenAI vs traditional ML: choose foundation-model patterns for generation and reasoning tasks, and traditional ML patterns for structured prediction, forecasting, and classification.
  • RAG and grounding: look for retrieval, embeddings, vector search, knowledge bases, and source attribution when the scenario needs current or private information.
  • Responsible AI: watch for bias, toxicity, hallucination, human review, explainability, privacy, transparency, and safe-use constraints.
  • Governance boundary: match IAM, encryption, auditability, data residency, compliance, and model-access controls to the sensitivity of the workload.

AIF-C01 readiness map

AreaWhat strong readiness looks like
AI and ML fundamentalsYou can distinguish supervised learning, unsupervised learning, deep learning, inference, training, evaluation, and common metrics.
Generative AI fundamentalsYou can explain foundation models, prompts, embeddings, tokens, hallucinations, model modalities, and model selection.
Foundation model applicationsYou can identify when to use RAG, agents, knowledge bases, prompt templates, customization, and managed AWS AI services.
Responsible AIYou can apply fairness, privacy, transparency, human oversight, and safety controls to realistic business scenarios.
Security and governanceYou can protect AI workloads with least privilege, encryption, monitoring, data controls, and compliant service configuration.

How to use the AIF-C01 simulator efficiently

  1. Start with domain drills so you can separate AI basics from AWS-specific service choices.
  2. Review every miss until you can explain why the best answer fits the use case, the data, and the governance constraint.
  3. Move into mixed sets once you can switch between model types, prompt patterns, RAG, guardrails, and compliance scenarios without hesitation.
  4. Finish with timed runs so the 90-minute pace feels normal before test day.

Final 7-day AIF-C01 practice sequence

DayPractice focus
7Open the web app for a timed mixed set, then use the public diagnostic page if you need to group misses by AI concept, AWS service, and governance topic.
6Drill AI/ML fundamentals, model lifecycle, evaluation concepts, and data-quality reasoning.
5Drill generative AI concepts, prompt patterns, embeddings, RAG, agents, and foundation-model applications.
4Drill responsible AI, privacy, security, compliance, and governance scenarios.
3Complete a timed mixed set and explain the use-case/service fit for every miss.
2Review confusing service pairs and AI terms, especially Bedrock, SageMaker AI, Transcribe, Translate, Comprehend, and Rekognition.
1Do a light confidence pass; avoid learning new AI terminology at the last minute.

When AIF-C01 practice is enough

If you can score above roughly 75% on several unseen mixed attempts and explain why each answer fits the use case, service boundary, and governance constraint, further drilling may produce memorization more than readiness. At that point, schedule the exam and keep the final review light.

Free study resources

Use this IT Mastery page for live practice, topic drills, timed mocks, explanations, and app access.

Web preview and premium practice

  • Web/public preview: a smaller web set so you can validate the question style and explanation depth.
  • Premium: interactive web-app practice with focused drills, mixed sets, timed mock exams, detailed explanations, and progress tracking across web and mobile.

AIF-C01 AI practitioner map

Use this map to connect individual items to the AWS AI Practitioner fundamentals decisions this practice page tests.

    flowchart LR
	  S1["Business AI scenario"] --> S2
	  S2["Identify AI ML or GenAI workload type"] --> S3
	  S3["Choose AWS AI service family"] --> S4
	  S4["Apply responsible AI and security basics"] --> S5
	  S5["Review cost data and governance"] --> S6
	  S6["Select next AWS AI route"]

Mini Glossary

  • Foundation model: Large pretrained model that can support many tasks through prompting or adaptation.
  • Inference: Using a trained model to produce a prediction or output.
  • Prompt: Input instruction or question given to a generative AI system.
  • Responsible AI: Practices that manage safety, fairness, transparency, privacy, and accountability.
  • SageMaker: AWS service family for building, training, deploying, and managing ML models.

In this section

AIP-C01
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