NetApp NS0-901 Certification Exam Sample Questions and Answers

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The best approach to pass your NetApp NS0-901 exam is to challenge and improve your knowledge. To test your learning and identify improvement areas with actual exam format, we suggest you practice with Premium NetApp NS0-901 Certification Practice Exam. The practice test is one of the most important elements of your NetApp Artificial Intelligence Expert (AI Expert) exam study strategy to discover your strengths and weaknesses, to improve your time management skills and to get an idea of the score you can expect.

NetApp NS0-901 (AI Expert) Sample Questions:

01. What is the primary difference between C-Series and A-Series storage for AI workloads?
a) C-Series is designed for high-performance workloads, while A-Series focuses on cost-efficiency for general storage.
b) A-Series provides GPU-based acceleration, while C-Series only supports CPU-based workloads.
c) C-Series supports both file and object-based storage, while A-Series is optimized for object storage.
d) A-Series is for smaller-scale AI workloads, while C-Series supports large-scale, high-performance AI applications.
 
02. Which of the following applications use AI in the healthcare industry?
(Choose two)
a) Predicting patient outcomes
b) Automating financial reporting
c) Diagnosing diseases
d) Managing hospital supply chains
 
03. Which of the following best describes the difference between data lakes, data warehouses, and lakehouses?
a) Data lakes store structured data, data warehouses store unstructured data, and lakehouses store only real-time data.
b) Data lakes store raw, unstructured data, data warehouses store structured data, and lakehouses combine the features of both.
c) Data lakes store metadata, data warehouses store transaction data, and lakehouses store archival data.
d) Data lakes store data in cloud storage, data warehouses store it in traditional databases, and lakehouses store it in external drives.
 
04. Which of the following platforms can be used to manage containerized AI workloads on Kubernetes?
(Choose two)
a) KubeFlow
b) TensorFlow Extended
c) Google VertexAI
d) RunAI
 
05. Which of the following techniques are used to maximize GPU utilization in AI workloads?
(Choose two)
a) Balancing compute and storage workloads efficiently
b) Scheduling GPU-intensive tasks during off-peak hours
c) Utilizing CPU-based workloads for all tasks
d) Using larger batch sizes
 
06. Which AI technology is used to generate new, never-before-seen content such as images or text?
a) Predictive AI
b) Generative AI
c) Reinforcement AI
d) Supervised AI
 
07. Which of the following are typical requirements for inferencing in AI models?
(Choose two)
a) Loading the model into memory
b) Pre-trained models
c) Extensive training data
d) Cloud-based inference only
 
08. Which of the following describes the impact of generative AI in content creation?
a) Generative AI can create new content such as text, images, and videos.
b) Generative AI only processes pre-existing content.
c) Generative AI predicts customer preferences without creating new content.
d) Generative AI analyzes data without generating content.
 
09. Which of the following platforms provides tools for model training and deployment specifically for AI workloads?
a) Google VertexAI
b) Domino Data Labs
c) RunAI
d) All of the above
 
10. Which storage protocols are commonly used for handling large-scale AI data?
(Choose two)
a) File-based systems
b) Object-based storage
c) POSIX-based file systems
d) Parallel file systems

Solutions:

Question: 01

Answer: a

Question: 02

Answer: a, c

Question: 03

Answer: b

Question: 04

Answer: a, d

Question: 05

Answer: a, b

Question: 06

Answer: b

Question: 07

Answer: a, b

Question: 08

Answer: a

Question: 09

Answer: d

Question: 10

Answer: b, d

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