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The AWS Certified AI Practitioner (AIF-C01) practice exam is intended for individuals who are planning to take the exam and get certified. This updated release includes easy, medium, and hard practice sets to support learners at every stage of their AWS AI Practitioner (AIF-C01) prep. It also features a bonus set with 65 additional questions for extra exam readiness.

The Practice exam contains 390 unique high-quality real exam like test questions explanations and validates a individuals’s ability to complete the following tasks:

• Understand AI, ML, and generative AI concepts, methods, and strategies in general and on AWS.

• Understand the appropriate use of AI/ML and generative AI technologies to ask relevant questions within the candidate’s organization.

• Determine the correct types of AI/ML technologies to apply to specific use cases.

• Use AI, ML, and generative AI technologies responsibly.

• AI, ML, and generative AI concepts, methods, and strategies in general and on AWS.

Sample Question

Which AWS service can be used to label training data for supervised machine learning?

Option 1 - AWS CodeCommit

Option 2 - Amazon SageMaker Ground Truth

Option 3 - AWS Glue

Option 4 - Amazon Rekognition

Recommended AWS knowledge

The individual should have the following AWS knowledge:

• Familiarity with the core AWS services (for example, Amazon EC2, Amazon S3, AWS Lambda, and Amazon SageMaker) and AWS core services use cases

• Familiarity with the AWS shared responsibility model for security and compliance in the AWS Cloud

• Familiarity with AWS Identity and Access Management (IAM) for securing and controlling access to AWS resources

• Familiarity with the AWS global infrastructure, including the concepts of AWS Regions, Availability Zones, and edge locations

• Familiarity with AWS service pricing models

The Practice tests has the following content domains and weightings:

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

• Domain 2: Fundamentals of Generative AI (24% of scored content)

• Domain 3: Applications of Foundation Models (28% of scored content)

• Domain 4: Guidelines for Responsible AI (14% of scored content)

• Domain 5: Security, Compliance, and Governance for AI Solutions (14% of scored content)