AIF-C01 FAQ — Common Questions (AWS Certified AI Practitioner)

What is AWS Certified AI Practitioner (AIF-C01)?

AIF-C01 is AWS’s foundational certification focused on AI and generative AI concepts plus how those concepts show up in AWS services and solution design.

If you want the fastest orientation, start with the section overview and keep the official exam guide from Resources open while you study.

Is AIF-C01 harder than Cloud Practitioner (CLF-C02)?

They are both foundational, but AIF-C01 leans harder into:

• AI/ML terminology and lifecycle
• Generative AI specifics (tokens, embeddings, RAG, prompting, evaluation)
• Responsible AI and governance (risk, transparency, security)

If you’re already comfortable with CLF-level AWS concepts, AIF-C01 is mostly about learning AI/GenAI language and patterns.

What score do you need to pass AIF-C01?

AWS uses a scaled score (100–1000). The minimum passing score is 700.

How many questions and how much time?

• 65 total questions (50 scored + 15 unscored)
• 90 minutes
• Question types: multiple choice, multiple response, ordering, and matching

Are unscored questions marked on the exam?

No. AWS states that the 15 unscored questions are not identified during the exam, so treat every question as if it counts.

Do you need to code for AIF-C01?

Not deeply. You should be able to read simple technical descriptions and make good service/design choices (for example: use RAG to ground answers in proprietary documents), but the exam is not a programming test.

AWS also lists these as generally out of scope for this credential:

• Developing/coding AI/ML models and algorithms
• Feature engineering and hyperparameter tuning
• Building full AI/ML pipelines/infrastructure
• Deep math/statistics analysis
• Designing governance frameworks from scratch

Do you need ML math (linear algebra, calculus)?

No. You should understand concepts like overfitting, evaluation metrics, and training vs inference, but not detailed math derivations.

What AWS services should you know?

At a high level, be comfortable with:

• Amazon Bedrock and related features (Guardrails, Knowledge Bases, Agents, Model Evaluation)
• Amazon SageMaker AI (high-level role in building/training/deploying ML)
• Amazon Q Business and Amazon Q Developer
• Core AI services (for example: Textract, Comprehend, Rekognition, Transcribe, Translate, Polly, Lex, Kendra, Fraud Detector, Personalize)
• Security/governance controls (IAM, KMS, Macie, CloudTrail, Config, Audit Manager, Artifact)

Use the Cheat Sheet for a service-by-use-case map.

What is the best AIF-C01 study plan?

Use a timeline you can actually sustain:

• 30 days: intensive (fast learning + lots of practice)
• 60 days: balanced (time for review and reinforcement)
• 90 days: part-time (more repetition and spaced practice)

Build your 30/60/90-day schedule from the domain weights, then rotate between the Cheat Sheet and Resources so you keep concepts and official scope aligned.

Should you focus more on generative AI or traditional ML?

Both matter, but the domain weights skew toward gen AI + foundation model applications:

• Domain 2 (GenAI) + Domain 3 (Foundation model apps) = 52%

That said, Domain 1 fundamentals are the vocabulary everything else depends on.

How do you practice effectively for AIF-C01?

Follow a loop:

1. Read one objective area from the official exam guide in Resources
2. Review the matching service map in the Cheat Sheet
3. Write 3–5 “miss rules” from what you got wrong
4. Re-drill weak tasks 48–72 hours later (spaced repetition), using the official exam guide in Resources as your scope check