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Certified Artificial Intelligence Practitioner®

A vendor-neutral AI certification validating practical artificial intelligence and machine learning knowledge.

Licensing authority: CertNexus

Initial by examination
Certified Artificial Intelligence Practitioner®
Agreement
Acceptance of the CertNexus Candidate Agreement at the beginning of the examination is required for the examination to launch.
Certification
Earn the certification by passing the AIP-210 examination; training, readiness assessment and test preparation are not separate mandatory examinations.
Delivery exclusions
The current handbook excludes residents of Iran, North Korea, Syria and Sudan; delivery and seat availability remain subject to the published provider policies.
Eligibility
No application fee, supporting documentation or other eligibility verification measures for examination eligibility; no examination prerequisites and no mandatory training. The published background knowledge, course list and 1–3 years of professional exposure describe preparation/target candidates and are not additional examination dependencies.
Evidence Claim Ids
["national-caip-route-adoption-20261025","national-caip-registration-20261025","national-caip-assessment-20261025"]
Identification
Generally bring registration confirmation and a government-issued ID; the administering testing center determines the specific acceptable identification requirements.
Scheduling
Rolling appointments may be scheduled in advance or on the testing day, subject to availability; create or use a Pearson VUE account, select the exam from the catalog, schedule and pay or redeem a voucher. In-person Pearson VUE and Pearson OnVUE proctoring are published options.
Vouchers
Vouchers are non-refundable, non-transferable and non-exchangeable, and expire 18 months from purchase unless otherwise noted; all attempts must use a valid voucher.

Certified Artificial Intelligence Practitioner®

Provider
Pearson VUE
Format
Proctored multiple-choice / multiple-response examination; in person at Pearson VUE test centers or online through Pearson OnVUE.
Exam questions
Scored questions: 80.
Time limit
120 minutes, including 5 minutes for the Candidate Agreement and 5 minutes for the Pearson VUE tutorial.
Passing score
60% or 59% depending on exam form; forms have been statistically equated.
Examination outline
  • Understanding the Artificial Intelligence Problem (26%)
    • Describe how artificial intelligence and machine learning are used to solve business problems
    • Analyze the use cases of ML algorithms to rank them by their success probability
    • Research Learning Systems
    • Analyze machine learning system use cases
    • Communicate with stakeholders
    • Identify potential ethical concerns
  • Engineering Features for Machine Learning (20%)
    • Recognize relative impact of data quality and size to algorithms
    • Explain data collection/transformation process in ML workflow
    • Work with textual, numerical, audio, or video data formats
    • Transform numerical and categorical data
    • Address business risks, ethical concerns, and related concepts in data exploration/feature engineering
  • Training and Tuning ML Systems and Models (24%)
    • Design machine and deep learning models
    • Optimize the algorithm
    • Train, validate, and test data subsets
    • Evaluate the model
    • Address business risks, ethical concerns, and related concepts in training and tuning
  • Operationalizing ML Models (30%)
    • Deploy a model
    • Secure a pipeline (includes maintenance)
    • Maintain the model postproduction
    • Address business risks, ethical concerns, and related concepts in operationalizing the model
Examination sources