Free study guide · 2026 edition
AWS Certified AI Practitioner
The AIF-C01 is the foundational AI/ML certification AWS launched in late 2024. It validates that you understand generative AI, Bedrock, SageMaker fundamentals, and responsible-AI guardrails — without requiring deep ML engineering experience.
Last updated: May 15, 2026Author: FactualMinds AWS ArchitectsReviewed by: Palaniappan P · AWS Solutions Architect — Professional
Exam code
AIF-C01
Duration
90 minutes
Questions
65
Cost
$100 USD
Passing score
700 / 1000
Format
Multiple choice and multiple response
Valid for
3 years
Recommended experience
6 months of exposure to AWS and basic AI/ML concepts — no hands-on ML engineering required
Exam domains
5 domains · 25 topics
1 Fundamentals of AI and ML
20%
Fundamentals of AI and ML
- Difference between AI, machine learning, deep learning, and generative AI
- Supervised, unsupervised, and reinforcement learning at a conceptual level
- Training vs inference; the role of datasets, features, and labels
- Common AI/ML use cases: classification, regression, recommendation, anomaly detection
- Model performance metrics: accuracy, precision, recall, F1, AUC at a high level
2 Fundamentals of Generative AI
24%
Fundamentals of Generative AI
- What foundation models are; tokens, embeddings, context windows, temperature
- Prompt engineering basics: zero-shot, few-shot, chain-of-thought
- Retrieval-augmented generation (RAG) at a conceptual level
- Fine-tuning vs RAG vs prompt engineering trade-offs
- Multimodal models: text, image, video, audio inputs and outputs
3 Applications of Foundation Models
28%
Applications of Foundation Models
- Amazon Bedrock: foundation model access, Knowledge Bases, Agents, Guardrails
- Amazon Q Business, Q Developer, Q in QuickSight, Q in Connect — when each fits
- Amazon Nova family — Micro, Lite, Pro, Premier, Canvas, Reel
- Amazon SageMaker JumpStart for pre-trained model deployment
- Embedding models and vector stores: S3 Vectors, OpenSearch, Aurora pgvector
4 Guidelines for Responsible AI
14%
Guidelines for Responsible AI
- Bias, fairness, explainability — concepts and AWS service support
- Bedrock Guardrails: content filters, PII detection, contextual grounding, automated reasoning checks
- AWS AI Service Cards and model documentation
- Watermarking outputs: Nova Canvas and Reel invisible watermarks
- Data residency, training-data privacy, customer-content protections on Bedrock and Q
5 Security, Compliance, and Governance for AI Solutions
14%
Security, Compliance, and Governance for AI Solutions
- IAM for AI workloads — least-privilege model access, KMS encryption
- PrivateLink and VPC endpoints for Bedrock and SageMaker
- Compliance regimes that recognize Bedrock and SageMaker (HIPAA, SOC 2, ISO 27001)
- Audit trails: CloudTrail logging for Bedrock and Q
- AI/ML model risk management at an organizational level
Why AIF-C01 exists
AWS launched the AI Practitioner certification in late 2024 to fill a gap in the certification ladder. Solutions Architect tracks assumed candidates understood AI/ML as architects of larger systems; ML Specialty (now retiring as MLS-C01) was deep-end ML engineering. AIF-C01 covers the literacy layer — what GenAI is, how Bedrock works, how to evaluate responsible-AI risks — without requiring hands-on training of models.
For consultants, sales engineers, product managers, and engineering managers shipping AI features on AWS, this is the certification that proves you can speak the language credibly.
Recommended 3-week study plan
Week 1 — Foundations (10 hours) Skim the AWS AI Practitioner exam guide. Run through AWS Skill Builder’s Standard Plan for AIF-C01 learning plan (free). Watch the Generative AI on AWS Foundations digital course. Read the Amazon Bedrock User Guide introduction.
Week 2 — Hands-on Bedrock + Q (8 hours) Spend a Saturday in the Bedrock console: try a Knowledge Base on a 100-document S3 bucket; try Bedrock Guardrails with a couple of content-filter categories; try the inline-agent feature. In the AWS console, enable Amazon Q Developer Free Tier and ask it 10 questions about your AWS environment.
Week 3 — Practice exams + responsible AI (6 hours) Take the official AWS practice question set (free on Skill Builder). Take two Tutorial Dojo practice exams. Review every wrong answer and write a one-line explanation. Read the AWS Responsible AI whitepaper.
What this certification will NOT teach you
- Building production agents
- Operating SageMaker training pipelines
- Picking embedding dimensionality for your use case
- Cost-controlling per-tenant GenAI spend
For those, you need MLA-C01 (ML Engineer Associate) plus hands-on experience.
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Frequently asked questions
Is AIF-C01 worth taking if I already have SAA-C03?
Yes — AIF-C01 covers AI/ML and GenAI concepts the Solutions Architect Associate does not, and it is a useful stepping stone if you plan to take MLA-C01 (Machine Learning Engineer Associate) or the Generative AI Specialty when it reaches GA. The exam takes most candidates 2–3 weeks of focused study at $100 — high ROI for the time.
How is AIF-C01 different from MLA-C01?
AIF-C01 (AI Practitioner) is foundational — concepts, services, and responsible-AI guidelines, no hands-on ML engineering. MLA-C01 (Machine Learning Engineer Associate) is hands-on — model selection, training, deployment, MLOps pipelines, monitoring. Take AIF-C01 first if you are new to ML; jump straight to MLA-C01 if you have built and deployed ML systems before.
Does AIF-C01 expire?
Yes — like all AWS certifications, AIF-C01 is valid for 3 years. AWS allows recertification by passing the latest exam version or earning a higher-level certification in the same track (MLA-C01 currently extends AIF-C01).
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