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CertNexus AIP-210 Exam Questions
- Topic 1: Identify potential ethical concerns/ Analyze machine learning system use cases
- Topic 2: Train, validate, and test data subsets/ Training and Tuning ML Systems and Models
- Topic 3: Recognize relative impact of data quality and size to algorithms/ Engineering Features for Machine Learning
- Topic 4: Transform numerical and categorical data/ Address business risks, ethical concerns, and related concepts in operationalizing the model
- Topic 5: Understanding the Artificial Intelligence Problem/ Analyze the use cases of ML algorithms to rank them by their success probability
- Topic 6: Address business risks, ethical concerns, and related concepts in training and tuning/ Work with textual, numerical, audio, or video data formats
- Topic 7: Design machine and deep learning models/ Explain data collection/transformation process in ML workflow
Free CertNexus AIP-210 Exam Actual Questions
Note: Premium Questions for AIP-210 were last updated On Mar. 18, 2026 (see below)
A data scientist is tasked to extract business intelligence from primary data captured from the public. Which of the following is the most important aspect that the scientist cannot forget to include?
Data privacy is the right of individuals to control how their personal data is collected, used, shared, and protected. It also involves complying with relevant laws and regulations that govern the handling of personal data. Data privacy is especially important when extracting business intelligence from primary data captured from the public, as it may contain sensitive or confidential information that could harm the individuals if misused or breached .
R-squared is a statistical measure that:
R-squared is a statistical measure that indicates how well a regression model fits the data. R-squared is calculated by dividing the explained variance by the total variance. The explained variance is the amount of variation in the dependent variable that can be attributed to the independent variables. The total variance is the amount of variation in the dependent variable that can be observed in the data. R-squared ranges from 0 to 1, where 0 means no fit and 1 means perfect fit.
Which of the following describes a benefit of machine learning for solving business problems?
Increasing the speed of analysis is a benefit of machine learning for solving business problems. Machine learning is a branch of artificial intelligence that involves creating systems that can learn from data and make predictions or decisions. Machine learning can help increase the speed of analysis by automating and optimizing various tasks, such as data processing, feature extraction, model training, model evaluation, or model deployment. Machine learning can also help handle large and complex data sets that may be difficult or impractical to analyze manually or with traditional methods.
Which of the following equations best represent an LI norm?
An L1 norm is a measure of distance or magnitude that is defined as the sum of the absolute values of the components of a vector. For example, if x and y are two components of a vector, then the L1 norm of that vector is |x| + |y|. The L1 norm is also known as the Manhattan distance or the taxicab distance, as it represents the shortest path between two points in a grid-like city.
Which of the following can benefit from deploying a deep learning model as an embedded model on edge devices?
Latency is the time delay between a request and a response. Latency can affect the performance and user experience of an application, especially when real-time or near-real-time responses are required. Deploying a deep learning model as an embedded model on edge devices can reduce latency, as the model can run locally on the device without relying on network connectivity or cloud servers. Edge devices are devices that are located at the edge of a network, such as smartphones, tablets, laptops, sensors, cameras, or drones.
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