CertNexus Certified Artificial Intelligence Practitioner (CAIP) - AIP-210 Exam Questions

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.

A. They are usually very good at solving non-linear problems. B. They are usually binary classifiers. C. They usually compromise on model accuracy for the sake of interpretability. D. They are usually referred to as "black box" models. E. They are usually easier to explain to business stakeholders.

A. Delete entire columns that contain any missing features. B. Fill in missing features with the average of observed values for that feature in the entire dataset. C. Delete entire rows that contain any missing features. D. Fill in missing features with random values for that feature in the training set.

A. The application was migrated from on-premise to a public cloud. B. The team set flawed expectations when training the model. C. The training data used was inaccurate. D. The AI model was trained in winter and applied in summer.

A. Skip-gram B. PCA C. Lemmatization D. TF-IDF E. t-SNE F. Tokenization

A. Support-vector machines (SVM) B. Generative adversarial networks (GAN) C. Recurrent neural networks (RNN) D. Long short-term memory (LSTM) networks

A. Cybersecurity B. Data privacy C. Data security D. Cyberprotection

A. Avoiding mechanisms to explain and justify automated decisions. B. Understanding, documenting, and displaying data lineage. C. Collecting and processing the largest amount of data possible. D. Utilizing quasi-identifiers and non-unique identifiers, alone or in combination.

A. Model complexity B. Refactoring C. Boundary erosion D. Documentation readability E. Design anti-patterns

A. Kurtosis B. Variance C. Missingness D. Skewness