Exam Overview
Exam Details
- Code: AIF-C01
- Level: Foundational
- Duration: 90 minutes
- Questions: 65
- Passing Score: 700/1000
- Cost: ~$100 USD
- Validity: 3 years
👤 Who It's For
Designed for individuals who use or interact with AI/ML solutions on AWS but do not necessarily build them. Recommended (not required): up to 6 months of exposure to AI/ML technologies on AWS. Ideal for business analysts, product managers, sales/marketing, IT support, and anyone starting the AWS AI learning path.
📊 Exam Domains
| Domain | Weight |
|---|---|
| 1. Fundamentals of AI and ML | 20% |
| 2. Fundamentals of Generative AI | 24% |
| 3. Applications of Foundation Models | 28% |
| 4. Guidelines for Responsible AI | 14% |
| 5. Security, Compliance, and Governance for AI Solutions | 14% |
Domain weights reflect the AIF-C01 exam guide. Always confirm against the latest official guide.
📚 Key Topics
AI/ML Fundamentals
- AI vs. ML vs. deep learning vs. generative AI
- Supervised, unsupervised, and reinforcement learning
- Training data, features, labels, inference
- Common use cases: classification, regression, forecasting, NLP, computer vision
- Model evaluation basics (accuracy, precision, recall)
Generative AI & Foundation Models
- Foundation models (FMs) and large language models (LLMs)
- Tokens, embeddings, context windows, temperature
- Prompt engineering basics; zero/few-shot prompting
- Retrieval-Augmented Generation (RAG)
- Fine-tuning vs. prompt engineering vs. RAG trade-offs
Responsible AI
- Bias, fairness, transparency, explainability
- Hallucinations and how to mitigate them
- Human-in-the-loop and guardrails
- Amazon Bedrock Guardrails; SageMaker Clarify
Security & Governance
- Data privacy: inputs/outputs not used to train FMs
- IAM for AI services; least privilege
- Encryption, VPC endpoints/PrivateLink for AI workloads
- Governance, compliance, and audit considerations
☁️ Key AWS Services to Know
| Service | What to know |
|---|---|
| Amazon Bedrock | Managed access to foundation models; RAG (Knowledge Bases), Agents, Guardrails |
| Amazon SageMaker AI | Build/train/deploy ML models; SageMaker Clarify (bias), JumpStart |
| Amazon Q | Generative AI assistant for business and builders |
| Amazon Comprehend | NLP: sentiment, entities, PII detection |
| Amazon Rekognition | Image and video analysis |
| Amazon Transcribe / Polly / Translate | Speech-to-text, text-to-speech, translation |
| Amazon Textract | Extract text and data from documents |
| Amazon Kendra | Intelligent enterprise search |
📋 Study Checklist
Progress0%
- Read the official AIF-C01 exam guide
- Understand AI vs ML vs deep learning vs generative AI
- Learn foundation model concepts: tokens, embeddings, prompts
- Understand RAG vs fine-tuning vs prompt engineering trade-offs
- Explore Amazon Bedrock: models, Knowledge Bases, Guardrails, Agents
- Review responsible AI: bias, fairness, explainability, hallucinations
- Learn AI security & governance: data privacy, IAM, encryption
- Know the AWS AI/ML service portfolio and use cases
- Complete the AWS Skill Builder AI Practitioner learning plan
- Score 75%+ on practice exams before booking