Artificial Intelligence Professional Certificate (CAIPC)

$100.00 USD

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Become an Artificial Intelligence Professional Certified.

Artificial Intelligence Professional Certificate is available to take or re-take online.

Exam Code: CAIPC 

Exam format

  • Multiple choice
  • 40 questions
  • Passing score: 80%
  • 60 minutes duration
  • Closed book
  • Unproctored exam delivered through

You will have two attempts within 180 calendar days after you receive your initial welcome email to pass the test at no cost.


Please read the following carefully before proceeding:

  • You may take the exam immediately or within 6 months from payment date.
  • Once the exam is purchased and taken you won’t be eligible for a refund.

Retake Policy

Each exam purchase includes 1 free retake.

Become an Artificial Intelligence Professional Certified.

In 1959, Arthur Samuel, a computer scientist who pioneered the study of Artificial Intelligence, described machine learning as "the study that gives computers the ability to learn without being explicitly programmed." Alan Turing's seminal paper (Turing, 1950) introduced a benchmark standard for demonstrating machine intelligence. A machine has to be intelligent and responsive in a manner that cannot be differentiated from that of a human being.

Machine Learning is an application of Artificial Intelligence where a computer/machine learns from past experiences (input data) and makes future predictions. The performance of such a system should be at least at human level.

This certification focuses on clustering problems for unsupervised machine learning with K-Means algorithm. For Supervised machine learning, we will describe the classification problem with a demonstration of the design trees algorithm and the regression one with an example of linear regression.

  • Anyone interested in expanding their knowledge in Artificial Intelligence and Machine Learning
  • Engineers
  • Analysts
  • Marketing Managers
  • Data Analysts
  • Data Scientists, 
  • Data Stewards
  • Anyone interested in Data Mining and Machine Learning techniques
  • Understand the fundamentals of Artificial Intelligence and Machine Learning
  • Describe the methods of Machine Learning: supervised and unsupervised
  • Use the data analysis for Decision-Making
  • Understand the limits of algorithms
  • Understand and grasp Python programming, essential mathematics knowledge in AI, and basic programming method

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