The AWS Certified AI Practitioner (AIF-C01) validates foundational knowledge of AI, machine learning, generative AI, and responsible AI on AWS. It is a foundational‑level exam that tests conceptual understanding, service selection, and governance of AI solutions.

Exam Domains & Sample Topics:

- Fundamentals of AI and ML (20%)

  Topics: AI vs. ML vs. deep learning vs. generative AI, Supervised, unsupervised, and reinforcement learning, Common ML algorithms (classification, regression, clustering), ML development lifecycle (data collection, preparation, training, evaluation, deployment, monitoring), Practical AI use cases (forecasting, recommendation, anomaly detection, computer vision, NLP)

- Fundamentals of Generative AI (24%)

  Topics: Core concepts of large language models, Prompt engineering basics, Generative AI service offerings on AWS (e.g., Amazon Bedrock), Use cases for generative AI in business, Limitations and ethical considerations of generative AI

- Applications of Foundation Models (28%)

  Topics: Architecture of foundation models, Fine‑tuning and adaptation techniques, Mapping business problems to appropriate foundation models, Performance evaluation metrics for foundation models, Integration of foundation models with AWS services

- Guidelines for Responsible AI (14%)

  Topics: Fairness, bias detection, and mitigation, Inclusivity and diverse training data, Transparency, explainability, and interpretability, Safety, robustness, and human oversight, AWS tools for responsible AI (SageMaker Clarify, Bedrock Guardrails, Model Cards)

- Security, Compliance, and Governance for AI Solutions (14%)

  Topics: Identity and access management for AI workloads, Data encryption and protection in AI pipelines, Compliance frameworks relevant to AI (e.g., GDPR, HIPAA), Monitoring and audit logging for AI services, Governance features like model versioning and policy enforcement