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EXIN BCS Artificial Intelligence Essentials — Requirements & Free Practice

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EXIN BCS Artificial Intelligence Essentials

Professional certification of introductory AI principles and terminology and the benefits and risks of AI and machine learning, earned by passing its named examination.

Licensing authority: EXIN

Initial by examination
Applicability
Current official product adoption of English guide edition 202501 supports this evaluation date; unpublished award/route start and end dates remain null rather than being inferred from retrieval or examination launch.
Certification Requirement
Successful completion of this named examination; the complete certification requirement lists no separately assessed assignment or prior certification.
Delivery
Online candidates need a suitable computer, webcam, microphone, internet and proctoring environment. EXIN Anywhere advertises examination within 21 days of booking. Center availability varies. Trainers/employers must reschedule bookings they arranged.
Language
English
Requested Horizon
2026-11-25 through 2027-02-28: rolling examination subject to order window, system maintenance, proctoring and center availability; no individual future seat is reserved or guaranteed.
Training
Six contact hours including group assignments are recommended preparation, not mandatory attendance or a separate award requirement; self-study and classroom channels are available.

EXIN BCS Artificial Intelligence Essentials

Provider
EXIN
Format
Multiple-choice questions; no open book, notes or electronic equipment/aides.
Exam questions
Total questions: 20.
Time limit
30 minutes
Passing score
65% (13/20 questions)
Examination outline
  • An introduction to artificial intelligence (AI) and historical development (15%)
    • State the definitions of key AI terms
    • Identify key milestones in the development of AI
    • Identify different types of AI
  • Ethical and legal considerations (15%)
    • Identify the role of ethics in AI
    • State key ethical concerns in AI
    • Identify guiding principles in the use of ethical AI
  • Enablers of AI (15%)
    • List common examples of AI
    • Identify robotics in AI
    • Describe machine learning
    • Identify common machine learning concepts
  • Finding and using data in AI (20%)
    • State key data terms
    • Identify the characteristics of data quality
    • State the risks associated with handling data in AI
    • Identify data visualization techniques and tools
    • State key generative AI terms
    • Identify the use of data in the machine learning process
  • Using AI in your organization (20%)
    • Identify opportunities for AI in your organization
    • Identify project management approaches
    • Identify governance activities associated with implementing AI
  • Future planning and impact – human plus machine (15%)
    • Describe the roles and career opportunities presented by AI
    • Identify AI uses in the real world
    • Identify AI’s impact on society
    • Describe the future of AI
Examination sources