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Nutanix NCP-AI Exam Syllabus Topics:

Topic	Details
Topic 1	Configure a Nutanix Enterprise AI Environment: This domain focuses on operational setup including onboarding users, importing large language models, creating and securing API endpoints with keys, and delivering these endpoints to consumers.
Topic 2	Deploy a Nutanix Enterprise AI Environment: This domain covers initial deployment tasks including validating prerequisites, installing Enterprise AI components, and configuring DNS, URLs, and certificates for secure platform operation.
Topic 3	Perform Day 2 Operations: This domain addresses ongoing management including preparing application integration requirements, interpreting and optimizing performance metrics, monitoring access for anomalies, and selecting appropriate LLMs for optimal output.
Topic 4	Connect Applications to a Nutanix Enterprise AI Environment: This domain focuses on configuring and validating application connections to endpoints and monitoring endpoint metrics to track application usage and integration performance.
Topic 5	Troubleshoot a Nutanix Enterprise AI Environment: This domain covers diagnosing and resolving performance issues, resource utilization problems, cluster health check failures, and model import or endpoint creation errors.

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Nutanix Certified Professional - Artificial Intelligence v6.10 Sample Questions (Q65-Q70):

NEW QUESTION # 65
What is the least privileged user role within Nutanix Enterprise AI required to import a LLM?

A. Super Admin
B. NKP Admin
C. AI/ML User
D. AI/ML Admin

Answer: D

NEW QUESTION # 66
An administrator needs to download the Access token for installing Nutanix Enterprise AI.
Which method should the administrator take to satisfy this task?

A. Download from Nutanix portal.
B. Download the token from Prism Central marketplace.
C. Download from Docker hub account.
D. Download from the NAI helm chart bundle.

Answer: A

NEW QUESTION # 67
In a new instance of Nutanix Enterprise AI, what task must be completed to create an API key?

A. Create an endpoint first.
B. Provision an API key in NKP.
C. Provision a GPU worker node.
D. Download LLM and create endpoint.

Answer: A

NEW QUESTION # 68
A development team is building a new AI-powered customer service chatbot. They have successfully integrated an LLM from Hugging Face into their application via a Nutanix Enterprise AI (NAI) endpoint. The NAI administrator has confirmed the endpoint is in the 'Active' state, and internal sample requests run from the NAI Endpoint section return an 'accurate' response and 'Succeeded' status.
However, the developers report that the chatbot frequently provides vague or irrelevant answers to user queries, leading to low customer satisfaction scores. They describe the LLM's performance for this specific chatbot task as "suboptimal." What should the administrator advise the developers to do next to improve the quality of the LLM's responses for the customer service chatbot task?

A. Consult the Hugging Face documentation for the specific LLM to review its training data, intended use cases, and capabilities.
B. Instruct the administrator to check the Kubernetes pod logs for the endpoint to identify any CRASHLOOPBACKOFF or OOMKilled errors that might be affecting model inference.
C. Reseed the initial dataset and reimport the existing LLM within Nutanix Enterprise AI without implementing a RAG platform.
D. Increase the number of instances for the NAI endpoint to enhance performance and reduce latency.

Answer: A

NEW QUESTION # 69
A data-science team wants to test an unvalidated Hugging Face model within the NAI DashboarD.
Which option lets them onboard it?

A. Import Model - Using URL
B. Import Model - Using CURL
C. Marketplace app
D. NGC catalog

Answer: A

NEW QUESTION # 70
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