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
A classifier has been implemented to predict whether or not someone has a specific type of disease.
Considering that only 1% of the population in the dataset has this disease, which measures will work the BEST to evaluate this model?
- A . Mean squared error
- B . Precision and accuracy
- C . Precision and recall
- D . Recall and explained variance
Which of the following describes a typical use case of video tracking?
- A . Augmented dreaming
- B . Medical diagnosis
- C . Traffic monitoring
- D . Video composition
You are developing a prediction model. Your team indicates they need an algorithm that is fast and requires low memory and low processing power.
Assuming the following algorithms have similar accuracy on your data, which is most likely to be an ideal choice for the job?
- A . Deep learning neural network
- B . Random forest
- C . Ridge regression
- D . Support-vector machine
For each of the last 10 years, your team has been collecting data from a group of subjects, including their age and numerous biomarkers collected from blood samples. You are tasked with creating a prediction model of age using the biomarkers as input. You start by performing a linear regression using all of the data over the 10-year period, with age as the dependent variable and the biomarkers as predictors.
Which assumption of linear regression is being violated?
- A . Equality of variance (Homoscedastidty)
- B . Independence
- C . Linearity
- D . Normality
When should you use semi-supervised learning? (Select two.)
- A . A small set of labeled data is available but not representative of the entire distribution.
- B . A small set of labeled data is biased toward one class.
- C . Labeling data is challenging and expensive.
- D . There is a large amount of labeled data to be used for predictions.
- E . There is a large amount of unlabeled data to be used for predictions.
Which of the following can benefit from deploying a deep learning model as an embedded model on edge devices?
- A . A more complex model
- B . Guaranteed availability of enough space
- C . Increase in data bandwidth consumption
- D . Reduction in latency
Which of the following is the definition of accuracy?
- A . (True Positives + False Positives) / Total Predictions
- B . (True Positives + True Negatives) / Total Predictions
- C . True Positives / (True Positives + False Negatives)
- D . True Positives / (True Positives + False Positives)
Personal data should not be disclosed, made available, or otherwise used for purposes other than specified with which of the following exceptions? (Select two.)
- A . If it is for a good cause.
- B . If it was collected accidentally.
- C . If it was requested by the authority of law.
- D . If it was with consent of the person it is collected from.
- E . If the data is only collected once.
Which of the following sentences is TRUE about the definition of cloud models for machine learning pipelines?
- A . Data as a Service (DaaS) can host the databases providing backups, clustering, and high availability.
- B . Infrastructure as a Service (IaaS) can provide CPU, memory, disk, network and GPU.
- C . Platform as a Service (PaaS) can provide some services within an application such as payment applications to create efficient results.
- D . Software as a Service (SaaS) can provide AI practitioner data science services such as Jupyter notebooks.
In a self-driving car company, ML engineers want to develop a model for dynamic pathing.
Which of following approaches would be optimal for this task?
- A . Dijkstra Algorithm
- B . Reinforcement learning
- C . Supervised Learning.
- D . Unsupervised Learning
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