Last Updated: Oct 13, 2026
No. of Questions: 95 Questions & Answers with Testing Engine
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| Certification Vendor: | CertNexus |
|---|---|
| Exam Name: | CertNexus Certified Artificial Intelligence Practitioner (CAIP) Exam AIP-210 |
| Exam Number: | AIP-210 |
| Available Languages: | English |
| Exam Format: | Multiple Choice, Scenario-based Questions |
| Sample Questions: | DOWNLOAD DEMO |
| Section | Objectives |
|---|---|
| Data Preparation and Engineering | - Feature engineering - Data collection and cleaning - Data quality and bias considerations |
| Artificial Intelligence Fundamentals | - Types of AI systems (narrow, general, etc.) - AI concepts and terminology |
| Neural Networks and Deep Learning | - Deep learning applications - Basic neural network concepts |
| AI Solution Development Lifecycle | - Monitoring and maintenance - Model development workflow - Deployment considerations |
| Ethics, Governance, and Responsible AI | - Privacy and data protection - Bias and fairness in AI systems - Responsible AI principles |
| Machine Learning Fundamentals | - Unsupervised learning - Model training and evaluation concepts - Supervised learning |
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The CertNexus Certified Artificial Intelligence Practitioner (CAIP) is CertNexus's certification exam for CertNexus Certified Artificial Intelligence Practitioner (CAIP), at the Professional level. It validates applied skills employers hire for — a credential worth the effort.
The CertNexus Certified Artificial Intelligence Practitioner (CAIP) blueprint covers 6 domains — including Data Preparation and Engineering, AI Solution Development Lifecycle, Artificial Intelligence Fundamentals. The weightings are your efficiency map: heavy domains first. Every subtopic appears in the outline above.
Yes — download the free CertNexus Certified Artificial Intelligence Practitioner (CAIP) demo and judge the question quality before paying. Every purchase stays valid for 365 days with free updates throughout, renewable afterward at 50% off.
Which of the following is NOT an activation function?
Correct Answer: B 🗳️
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You have a dataset with thousands of features, all of which are categorical. Using these features as predictors, you are tasked with creating a prediction model to accurately predict the value of a continuous dependent variable. Which of the following would be appropriate algorithms to use? (Select two.)
Correct Answer: C,D 🗳️
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A company is developing a merchandise sales application The product team uses training data to teach the AI model predicting sales, and discovers emergent bias. What caused the biased results?
Correct Answer: B 🗳️
Explanation: Only visible for Exams-boost members. You can sign-up / login (it's free).
Which of the following sentences is true about model evaluation and model validation in ML pipelines?
Correct Answer: D 🗳️
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An HR solutions firm is developing software for staffing agencies that uses machine learning.
The team uses training data to teach the algorithm and discovers that it generates lower employability scores for women. Also, it predicts that women, especially with children, are less likely to get a high-paying job.
Which type of bias has been discovered?
Correct Answer: A 🗳️
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