AIF-C01: AWS Certified AI Practitioner

Exam Information

Provider: AWS (Amazon Web Services)
Exam Code: AIF-C01
Official Exam Page: AWS AI Practitioner Certification
Exam Duration: 120 minutes
Number of Questions: 85 questions
Passing Score: 700/1000
Exam Format: Multiple choice, multiple response
Exam Cost: $75 USD
Validity: 3 years

Note Freshness

Prepared: January 2026 Last Updated: 2026-01-13

This is a newer certification (launched 2024). Content may evolve. Always verify with official documentation.

Overview

The AWS Certified AI Practitioner validates your understanding of AI/ML concepts, AWS AI/ML services, and responsible AI practices. This certification is designed for individuals who want to demonstrate foundational AI knowledge.

Target Audience:

Business analysts and data analysts
Product managers working with AI
Non-technical professionals who need to understand AI
Developers new to AI/ML
Anyone seeking foundational AI/ML knowledge on AWS

Prerequisites:

6 months of exposure to AWS AI/ML services (recommended)
Basic understanding of cloud computing concepts
Familiarity with data analytics concepts
No programming experience required

Study Materials

📋 Exam Objectives

Official exam domains and objectives outline

📚 Study Notes

Comprehensive study notes covering all exam topics

💡 Exam Tips

Exam strategies, common traps, and study advice

📖 Official Resources

Study Progress Tracker

Track your progress through the study materials.

Domain 1: Fundamentals of AI and ML (20%)

[ ] 1.1: Explain basic AI concepts and terminologies
[ ] 1.2: Identify practical use cases for AI
[ ] 1.3: Describe the ML development lifecycle

Domain 2: Fundamentals of Generative AI (24%)

[ ] 2.1: Explain the basic concepts of generative AI
[ ] 2.2: Understand the capabilities and limitations of generative AI
[ ] 2.3: Describe AWS services for generative AI

Domain 3: Applications of Foundation Models (28%)

[ ] 3.1: Describe design considerations for applications that use foundation models
[ ] 3.2: Choose appropriate foundation models for specific use cases
[ ] 3.3: Describe fine-tuning and prompt engineering strategies
[ ] 3.4: Explain Retrieval Augmented Generation (RAG)

Domain 4: Guidelines for Responsible AI (14%)

[ ] 4.1: Explain development practices for responsible AI
[ ] 4.2: Recognize the importance of transparent and explainable models

Domain 5: Security, Compliance, and Governance for AI Solutions (14%)

[ ] 5.1: Explain methods to secure AI systems
[ ] 5.2: Recognize governance and compliance regulations for AI systems

Additional Study Tasks

[ ] Explore Amazon Bedrock hands-on
[ ] Try Amazon Q for business use cases
[ ] Review AWS AI/ML service use cases
[ ] Complete AWS AI/ML learning paths
[ ] Practice with SageMaker Studio
[ ] Review responsible AI best practices

Exam Objectives →

AIF-C01: AWS Certified AI Practitioner ​

Exam Information ​

Overview ​

Study Materials ​

📋 Exam Objectives ​

📚 Study Notes ​

💡 Exam Tips ​

📖 Official Resources ​

Study Progress Tracker ​

Domain 1: Fundamentals of AI and ML (20%) ​

Domain 2: Fundamentals of Generative AI (24%) ​

Domain 3: Applications of Foundation Models (28%) ​

Domain 4: Guidelines for Responsible AI (14%) ​

Domain 5: Security, Compliance, and Governance for AI Solutions (14%) ​

Additional Study Tasks ​