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CertNexus AIP-210 Exam Syllabus Topics:

Topic	Details
Topic 1	Understanding the Artificial Intelligence Problem Analyze the use cases of ML algorithms to rank them by their success probability
Topic 2	Transform numerical and categorical data Address business risks, ethical concerns, and related concepts in operationalizing the model
Topic 3	Recognize relative impact of data quality and size to algorithms Engineering Features for Machine Learning
Topic 4	Train, validate, and test data subsets Training and Tuning ML Systems and Models
Topic 5	Address business risks, ethical concerns, and related concepts in training and tuning Work with textual, numerical, audio, or video data formats
Topic 6	Identify potential ethical concerns Analyze machine learning system use cases

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CertNexus Certified Artificial Intelligence Practitioner (CAIP) Sample Questions (Q69-Q74):

NEW QUESTION # 69
Which three security measures could be applied in different ML workflow stages to defend them against malicious activities? (Select three.)

A. Use Secrets Manager to protect credentials.
B. Use max privilege to control access to ML artifacts.
C. Disable logging for model access.
D. Monitor model degradation.
E. Launch ML Instances In a virtual private cloud (VPC).
F. Use data encryption.

Answer: A,E,F

Explanation:
Explanation
Security measures can be applied in different ML workflow stages to defend them against malicious activities, such as data theft, model tampering, or adversarial attacks. Some of the security measures are:
Launch ML Instances In a virtual private cloud (VPC): A VPC is a logically isolated section of a cloud provider's network that allows users to launch and control their own resources. By launching ML instances in a VPC, users can enhance the security and privacy of their data and models, as well as restrict the access and traffic to and from the instances.
Use data encryption: Data encryption is the process of transforming data into an unreadable format using a secret key or algorithm. Data encryption can protect the confidentiality, integrity, and availability of data at rest (stored in databases or files) or in transit (transferred over networks). Data encryption can prevent unauthorized access, modification, or leakage of sensitive data.
Use Secrets Manager to protect credentials: Secrets Manager is a service that helps users securely store, manage, and retrieve secrets, such as passwords, API keys, tokens, or certificates. Secrets Manager can help users protect their credentials from unauthorized access or exposure, as well as rotate them automatically to comply with security policies.

NEW QUESTION # 70
Which of the following tests should be performed at the production level before deploying a newly retrained model?

A. Unit test
B. A/Btest
C. Security test
D. Performance test

Answer: D

Explanation:
Explanation
Performance testing is a type of testing that should be performed at the production level before deploying a newly retrained model. Performance testing measures how well the model meets the non-functional requirements, such as speed, scalability, reliability, availability, and resource consumption. Performance testing can help identify any bottlenecks or issues that may affect the user experience or satisfaction with the model. References: [Performance Testing Tutorial: What is, Types, Metrics & Example], [Performance Testing for Machine Learning Systems | by David Talby | Towards Data Science]

NEW QUESTION # 71
An AI system recommends New Year's resolutions. It has an ML pipeline without monitoring components.
What retraining strategy would be BEST for this pipeline?

A. Periodically every year
B. When concept drift is detected
C. When data drift is detected
D. Periodically before New Year's Day and after New Year's Day

Answer: A

NEW QUESTION # 72
Which of the following approaches is best if a limited portion of your training data is labeled?

A. Dimensionality reduction
B. Reinforcement learning
C. Semi-supervised learning
D. Probabilistic clustering

Answer: C

Explanation:
Explanation
Semi-supervised learning is an approach that is best if a limited portion of your training data is labeled.
Semi-supervised learning is a type of machine learning that uses both labeled and unlabeled data to train a model. Semi-supervised learning can leverage the large amount of unlabeled data that is easier and cheaper to obtain and use it to improve the model's performance. Semi-supervised learning can use various techniques, such as self-training, co-training, or generative models, to incorporate unlabeled data into the learning process.

NEW QUESTION # 73
Which of the following unsupervised learning models can a bank use for fraud detection?

A. Anomaly detection
B. DB5CAN
C. Hierarchical clustering
D. k-means

Answer: A

Explanation:
Explanation
Anomaly detection is an unsupervised learning technique that identifies outliers or abnormal patterns in data, which can be useful for fraud detection. Anomaly detection algorithms can learn the normal behavior of transactions and flag the ones that deviate significantly from the norm, indicating possible fraud.

NEW QUESTION # 74
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Pass Guaranteed CertNexus - AIP-210 - Useful Latest CertNexus Certified Artificial Intelligence Practitioner (CAIP) Dumps Files

CertNexus AIP-210 Exam Syllabus Topics:

New Latest AIP-210 Dumps Files | Valid CertNexus AIP-210 Reliable Exam Pattern: CertNexus Certified Artificial Intelligence Practitioner (CAIP)

CertNexus Certified Artificial Intelligence Practitioner (CAIP) Sample Questions (Q69-Q74):

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