CertNexus AIP-210 CertNexus Certified Artificial Intelligence Practitioner (CAIP) Online Training
CertNexus AIP-210 Online Training
The questions for AIP-210 were last updated at Nov 19,2024.
- Exam Code: AIP-210
- Exam Name: CertNexus Certified Artificial Intelligence Practitioner (CAIP)
- Certification Provider: CertNexus
- Latest update: Nov 19,2024
R-squared is a statistical measure that:
- A . Combines precision and recall of a classifier into a single metric by taking their harmonic mean.
- B . Expresses the extent to which two variables are linearly related.
- C . Is the proportion of the variance for a dependent variable thaf’ s explained by independent variables.
- D . Represents the extent to which two random variables vary together.
Which of the following equations best represent an LI norm?
- A . |x| + |y|
- B . |x|+|y|^2
- C . |x|-|y|
- D . |x|^2+|y|^2
Which of the following statements are true regarding highly interpretable models? (Select two.)
- A . They are usually binary classifiers.
- B . They are usually easier to explain to business stakeholders.
- C . They are usually referred to as "black box" models.
- D . They are usually very good at solving non-linear problems.
- E . They usually compromise on model accuracy for the sake of interpretability.
Which two of the following decrease technical debt in ML systems? (Select two.)
- A . Boundary erosion
- B . Design anti-patterns
- C . Documentation readability
- D . Model complexity
- E . Refactoring
Which of the following describes a neural network without an activation function?
- A . A form of a linear regression
- B . A form of a quantile regression
- C . An unsupervised learning technique
- D . A radial basis function kernel
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/(48+37)
- B . 37/(37+8)
- C . 37/(37+7)
- D . (48+37)/100
Given a feature set with rows that contain missing continuous values, and assuming the data is normally distributed, what is the best way to fill in these missing features?
- A . Delete entire rows that contain any missing features.
- B . Fill in missing features with random values for that feature in the training set.
- C . Fill in missing features with the average of observed values for that feature in the entire dataset.
- D . Delete entire columns that contain any missing features.
In addition to understanding model performance, what does continuous monitoring of bias and variance help ML engineers to do?
- A . Detect hidden attacks
- B . Prevent hidden attacks
- C . Recover from hidden attacks
- D . Respond to hidden attacks
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?
- A . The AI model was trained in winter and applied in summer.
- B . The application was migrated from on-premise to a public cloud.
- C . The team set flawed expectations when training the model.
- D . The training data used was inaccurate.
You train a neural network model with two layers, each layer having four nodes, and realize that the model is underfit.
Which of the actions below will NOT work to fix this underfitting?
- A . Add features to training data
- B . Get more training data
- C . Increase the complexity of the model
- D . Train the model for more epochs
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