• Exam Code: AIP-210
  • Exam Name: CertNexus Certified Artificial Intelligence Practitioner (CAIP)
  • Certification Provider: CertNexus
  • Corresponding Certification:Certified AI Practitioner
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CertNexus AIP-210 Exam Syllabus Topics:

TopicDetails
Topic 1
  • Address business risks, ethical concerns, and related concepts in training and tuning
  • Work with textual, numerical, audio, or video data formats
Topic 2
  • Design machine and deep learning models
  • Explain data collection
  • transformation process in ML workflow
Topic 3
  • Train, validate, and test data subsets
  • Training and Tuning ML Systems and Models

Reference: https://certnexus.com/certified-artificial-intelligence-practitioner-caip/

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CertNexus Certified Artificial Intelligence Practitioner (CAIP) Sample Questions:

The following confusion matrix is produced when a classifier is used to predict labels on a test dataset. How precise is the classifier?

  • A. (48+37)/100
  • B. 37/(37+8)
  • C. 37/(37+7)
  • D. 48/(48+37)
Reveal Solution  Discussion  0

Correct Answer: B  🗳️

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Which of the following is NOT an activation function?

  • A. Hyperbolic tangent
  • B. Additive
  • C. ReLU
  • D. Sigmoid
Reveal Solution  Discussion  0

Correct Answer: B  🗳️

Explanation: Only visible for TrainingDump members. You can sign-up / login (it's free).

When should the model be retrained in the ML pipeline?

  • A. Concept drift is detected in the pipeline.
  • B. More data become available for the training phase.
  • C. A new monitoring component is added.
  • D. Some outliers are detected in live data.
Reveal Solution  Discussion  0

Correct Answer: A  🗳️

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Your dependent variable Y is a count, ranging from 0 to infinity. Because Y is approximately log-normally distributed, you decide to log-transform the data prior to performing a linear regression.
What should you do before log-transforming Y?

  • A. Subtract the mean of Y from all the Y values.
  • B. Divide all the Y values by the standard deviation of Y.
  • C. Add 1 to all of the Y values.
  • D. Explore the data for outliers.
Reveal Solution  Discussion  0

Correct Answer: C  🗳️

Explanation: Only visible for TrainingDump members. You can sign-up / login (it's free).

Which of the following is NOT a valid cross-validation method?

  • A. Bootstrapping
  • B. K-fold
  • C. Stratification
  • D. Leave-one-out
Reveal Solution  Discussion  0

Correct Answer: C  🗳️

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