How to Pass AWS Certified AI Practitioner (AIF-C01) in 15 Days: Complete 2026 Roadmap
The AWS Certified AI Practitioner (AIF-C01) is the fastest-growing foundational AI certification in the cloud space. This complete 15-day study plan covers all five domains, the new question formats for 2026, key AWS services, and a day-by-day roadmap to help you pass on your first attempt.
Artificial intelligence is no longer a niche specialty — it is a core competency that every cloud professional needs to understand. AWS recognized this shift when it launched the AWS Certified AI Practitioner (AIF-C01) in 2024, creating a foundational-level certification designed for anyone who works with AI and ML solutions on AWS, regardless of whether they write code. By early 2026, AIF-C01 has become one of the fastest-growing AWS certifications, with tens of thousands of candidates sitting the exam each quarter. If you are a solutions architect, business analyst, project manager, or developer looking to validate your AI knowledge, this is the cert for you. And the best part? With a focused plan, you can be exam-ready in just 15 days.
What Is the AIF-C01 Certification?
The AWS Certified AI Practitioner (AIF-C01) is a foundational-level certification that validates your understanding of AI/ML concepts, generative AI technologies, and their practical applications on AWS. Unlike the Machine Learning Specialty (MLS-C01) or the newer Machine Learning Engineer Associate (MLA-C01), the AIF-C01 does not require you to write code, train models, or manage infrastructure. Instead, it tests whether you can make informed decisions about when and how to use AI services, understand the capabilities of foundation models, and apply responsible AI principles.
This certification is ideal for cloud practitioners, business stakeholders, pre-sales engineers, and anyone who needs to speak intelligently about AI in an AWS context. It sits alongside the Cloud Practitioner (CLF-C02) as a stepping stone — you do not need any prior AWS certification to take it.
Exam Format and 2026 Question Types
| Detail | Value |
|---|---|
| Number of Questions | 65 total (50 scored + 15 unscored pilot) |
| Time Limit | 90 minutes |
| Passing Score | 700 out of 1000 (scaled scoring) |
| Exam Cost | $100 USD |
| Delivery | Pearson VUE (testing center or online proctored) |
| Validity | 3 years |
| Prerequisite | None (6 months AI/ML experience recommended) |
New in 2026 — four question types. The AIF-C01 was one of the first AWS exams to introduce two new question formats beyond the traditional multiple choice and multiple response. Be prepared for:
| Question Type | What You Do | Example |
|---|---|---|
| Multiple Choice | Select 1 correct answer from 4 options | Which service performs real-time image moderation? |
| Multiple Response | Select 2 or 3 correct answers from 5-6 options | Which TWO are benefits of retrieval-augmented generation? |
| Ordering | Arrange steps in the correct sequence | Order the steps to implement a RAG pipeline with Bedrock Knowledge Bases |
| Matching | Match services/concepts to their descriptions or use cases | Match each AWS AI service to its primary function |
The Five Domains Explained
| Domain | Weight | Key Topics |
|---|---|---|
| 1. Fundamentals of AI and ML | 20% | Supervised vs unsupervised learning, classification, regression, clustering, reinforcement learning, ML pipeline stages, bias-variance tradeoff |
| 2. Fundamentals of Generative AI | 24% | Transformer architecture, tokenization, embeddings, foundation models, temperature/top-p, hallucination, prompt engineering basics |
| 3. Applications of Foundation Models | 28% | RAG, fine-tuning, prompt engineering, Amazon Bedrock, Bedrock Knowledge Bases, Bedrock Agents, Bedrock Guardrails, SageMaker JumpStart |
| 4. Guidelines for Responsible AI | 14% | Fairness, explainability, transparency, AI Service Cards, Model Cards, human-in-the-loop, SageMaker Clarify, Amazon A2I |
| 5. Security, Compliance, and Governance for AI | 14% | Data privacy, encryption (KMS), VPC endpoints, CloudTrail logging, shared responsibility model for AI, compliance frameworks, data governance |
Notice that Domains 2 and 3 together account for 52% of the exam — more than half your score. These are the generative AI and Bedrock-heavy domains, and they should receive the bulk of your study time. Domains 4 and 5 carry only 14% each, but do not skip them: responsible AI and security questions are where most candidates lose easy points because the concepts feel abstract until you study them deliberately.
Key AWS Services to Know
The AIF-C01 tests your knowledge of a specific set of AWS AI/ML services. You do not need to know how to code against their APIs, but you must understand what each service does, when to use it, and how it fits into the broader AI ecosystem.
| Service | Category | What It Does |
|---|---|---|
| Amazon Bedrock | Generative AI | Fully managed service to access foundation models (Claude, Llama, Titan, Mistral) via API without managing infrastructure |
| Amazon SageMaker AI | ML Platform | End-to-end ML platform for building, training, and deploying custom models |
| Amazon Q | AI Assistant | Enterprise AI assistant for business intelligence, code generation, and enterprise search |
| Amazon Rekognition | Vision AI | Image and video analysis — object detection, facial analysis, content moderation, text in images |
| Amazon Comprehend | NLP | Natural language processing — sentiment analysis, entity extraction, topic modeling, PII detection |
| Amazon Transcribe | Speech | Automatic speech recognition (ASR) — converts audio to text, supports custom vocabularies |
| Amazon Textract | Document AI | Extracts text, tables, and forms from scanned documents — goes beyond basic OCR |
| Amazon Polly | Speech | Text-to-speech — converts written text into lifelike spoken audio |
| Amazon Translate | Language | Neural machine translation for real-time and batch language translation |
| Amazon Kendra | Search | Intelligent enterprise search powered by ML — connects to multiple data sources |
15-Day Study Plan
This plan assumes 2-3 hours of study per day. If you have more time available, you can compress it. If you have less, stretch it to 20 days. The key is covering every domain systematically and leaving the final days for review and practice exams.
| Day | Focus Area | Activities |
|---|---|---|
| 1 | Exam Overview | Read the official exam guide. Understand all 5 domains and their weights. Take a diagnostic quiz on CertLand to identify weak areas. |
| 2 | Domain 1 — AI/ML Basics | Learn supervised vs unsupervised vs reinforcement learning. Understand classification, regression, and clustering. Study the ML pipeline: collect, prepare, train, evaluate, deploy. |
| 3 | Domain 1 — ML Concepts | Study bias-variance tradeoff, overfitting/underfitting, training/validation/test splits, evaluation metrics (accuracy, precision, recall, F1, AUC-ROC). Practice 30 Domain 1 questions on CertLand. |
| 4 | Domain 2 — GenAI Fundamentals | Learn transformer architecture (encoder-decoder), attention mechanism, tokenization, embeddings. Understand what makes foundation models different from traditional ML models. |
| 5 | Domain 2 — Inference Parameters | Study temperature, top-p, top-k, max tokens, stop sequences. Understand hallucination causes and mitigation. Learn prompt engineering: zero-shot, few-shot, chain-of-thought. |
| 6 | Domain 2 — Practice | Practice 40 Domain 2 questions on CertLand. Review explanations for every wrong answer. Focus on distinguishing between inference parameters. |
| 7 | Domain 3 — Amazon Bedrock | Deep dive into Bedrock: model families (Claude, Llama, Titan, Mistral, Cohere), model selection criteria, on-demand vs provisioned throughput. Explore the Bedrock console on AWS. |
| 8 | Domain 3 — RAG and Fine-Tuning | Learn RAG vs fine-tuning vs prompt engineering — when to use each. Study Bedrock Knowledge Bases (RAG), Bedrock Agents (agentic workflows), and SageMaker JumpStart for fine-tuning. |
| 9 | Domain 3 — Guardrails and Evaluation | Study Bedrock Guardrails: content filtering, topic denial, PII redaction, grounding checks. Learn evaluation metrics: ROUGE, BLEU, BERTScore, human evaluation. |
| 10 | Domain 3 — Practice | Practice 50 Domain 3 questions on CertLand. This is the highest-weighted domain — spend extra time reviewing explanations and taking notes on Bedrock features. |
| 11 | Domain 4 — Responsible AI | Study responsible AI principles: fairness, explainability, transparency, privacy, robustness. Learn AI Service Cards vs Model Cards. Understand SageMaker Clarify and Amazon A2I. |
| 12 | Domain 5 — Security and Governance | Study the shared responsibility model for AI services. Learn about VPC endpoints for Bedrock, KMS encryption, CloudTrail logging of model invocations, data governance, and compliance. |
| 13 | Domains 4 & 5 — Practice | Practice 40 questions covering Domains 4 and 5 on CertLand. Focus on distinguishing between similar concepts (Clarify vs A2I, Service Cards vs Model Cards). |
| 14 | Full Practice Exam | Take a full-length timed practice exam on CertLand (65 questions, 90 minutes). Score yourself, review every wrong answer, and make a list of topics to review on Day 15. |
| 15 | Review and Exam Day | Review your weak areas from Day 14. Re-read your notes on Bedrock features and responsible AI. Take a final 30-question sprint. Relax and get good sleep before the exam. |
Free Resources
You do not need to spend hundreds of dollars on preparation. AWS provides several free resources that are specifically designed for the AIF-C01:
- AWS Skill Builder — AI Practitioner Learning Plan: A free, curated set of courses covering all five exam domains. This is the single best starting point and takes approximately 15-20 hours to complete.
- AWS AI Practitioner Official Practice Question Set: A free set of 20 official practice questions available through AWS Skill Builder. These are written by the same team that writes the real exam.
- AWS AI Service Documentation: The Bedrock, SageMaker, and Comprehend documentation pages include excellent tutorials and conceptual overviews that align directly with exam content.
- AWS re:Invent and re:Post Videos: Search YouTube for "AWS re:Invent Bedrock" and "AWS re:Invent responsible AI" for deep-dive sessions from AWS engineers.
- AWS Whitepapers: The "Responsible Use of Machine Learning" whitepaper and the "AWS Well-Architected Framework — Machine Learning Lens" are both referenced in the exam guide.
Practice with CertLand
The AWS Certified AI Practitioner (AIF-C01) is one of the most accessible entry points into the world of AI certifications. With a focused 15-day plan, the right resources, and consistent practice, you can walk into your exam with confidence. The demand for AI-literate professionals is only growing — and this certification proves you have the foundational knowledge to contribute to AI projects on AWS. Good luck with your preparation!
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