Free PDF Quiz Network Appliance - Useful New NS0-901 Practice Questions

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Network Appliance NS0-901 Exam Syllabus Topics:

Section	Weight	Objectives
AI Common Challenges	22%	- Resource Management 1. Controlling costs and securing storage 2. Sizing storage and compute resources effectively - Traceability and Optimization 1. Ensuring traceability for code, data, and models 2. Maximizing performance in demanding AI workloads 3. Optimizing data access and movement
AI Lifecycle	27%	- Generative AI Concepts 1. Hallucinations 2. Retrieval Augmented Generation (RAG) 3. Fine-tuning - Data Preparation 1. XCP and CopySync 2. NetApp BlueXP Classification 3. Data aggregation and cleansing - Model Development 1. Model building 2. Fine-tuning workflows 3. Inferencing - Predictive AI vs. Generative AI 1. Distinction between predictive and generative AI 2. Large Language Models (LLMs) 3. Impact of generative content (text, images, video, decision-making)
AI Software Architectures	18%	- Scaling and Orchestration 1. Scaling AI workloads with Kubernetes 2. Leveraging BlueXP software tools - Development Tools 1. Jupyter notebooks vs. pipelines 2. NetApp DataOps Toolkit - MLOps and LLMOps Ecosystems 1. Understanding the software tools and platforms enabling AI at scale
AI Hardware Architectures	18%	- Infrastructure Topologies 1. Data aggregation and compute topologies - Networking and Storage 1. Network protocols for AI workloads 2. Storage architectures for AI - NetApp Architectures 1. BasePod 2. OVX architectures 3. SuperPOD
AI Overview	15%	- AI Convergence with HPC and Analytics 1. Leveraging shared infrastructure for AI, HPC, and analytics - AI Industry Applications 1. Digital twins 2. Healthcare applications 3. Agents - Machine Learning Fundamentals 1. Understand the relationship between AI, machine learning, and deep learning 2. Describe machine learning benefits - Algorithm Types 1. Reinforcement learning 2. Supervised learning 3. Unsupervised learning - AI Deployment Models 1. On-premises 2. Edge 3. Benefits and risks of each model 4. Cloud - Training vs. Inferencing vs. Predictions 1. Distinguish between training and inference workloads

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Network Appliance NetApp Certified AI Expert Exam Sample Questions (Q104-Q109):

NEW QUESTION # 104
Which of the following applications use AI in the healthcare industry? (Choose two)

A. Automating financial reporting
B. Predicting patient outcomes
C. Diagnosing diseases
D. Managing hospital supply chains

Answer: B,C

NEW QUESTION # 105
A training job on one of the NVIDIA DGX servers is running slowly. A performance engineer runs the 'dstat' command on the server and captures the following output during the job execution.
-total-cpu-usage- -dsk/total- -net/total- paging-- system-- usr sys idl wai hiq siq| read writ| recv send| in out | int csw 15 5 70 10 0 0| 1.2G 15.0M| 1.2G 12.0M| 0 0 | 15k 35k
14 6 69 11 0 0| 1.2G 14.3M| 1.2G 11.8M| 0 0 | 14k 33k
16 5 68 11 0 0| 1.2G 16.1M| 1.2G 13.1M| 0 0 | 16k 36k
The server is connected to the NetApp ASA via a 100GbE (12.5 GB/s) network.
What is the most likely performance bottleneck based on this data?

A. The server's network interface is saturated.
B. The storage system (ASA) is unable to provide sufficient read throughput.
C. The server's CPU is overloaded.
D. The application is experiencing excessive memory paging.

Answer: A

NEW QUESTION # 106
A security administrator is reviewing the configuration of a production ONTAP cluster after a compliance audit. The audit requires that all volumes containing financial data must be protected against ransomware. The administrator runs a command to check the status of Autonomous Ransomware Protection (ARP) on a critical volume.
The command and its output are as follows:
cluster-1::> security ransomware anti-ransomware show -vserver svm_finance -volume finance_q1_data Vserver: svm_finance Volume: finance_q1_data Autonomous Ransomware Protection Status: disabled Learning Mode: normal Dry Run Mode: false Action on Detection: notify Based on this output, what is the primary security risk for the 'finance_q1_data' volume?

A. The action on detection is set only to "notify," which will not block the attack.
B. The learning mode is set to "normal," which may not detect zero-day attacks.
C. The volume is not part of any Snapshot schedule.
D. The volume is vulnerable to ransomware because Autonomous Ransomware Protection is not enabled.

Answer: D

NEW QUESTION # 107
Which of the following describes the impact of generative AI in content creation?

A. Generative AI only processes pre-existing content.
B. Generative AI predicts customer preferences without creating new content.
C. Generative AI analyzes data without generating content.
D. Generative AI can create new content such as text, images, and videos.

Answer: D

NEW QUESTION # 108
A media company is building a new generative AI service. The project has two main components:
1. Data Lake & Fine-Tuning: A 300 TB repository of unstructured data (videos, images, text) stored as objects will be used to fine-tune a foundational model. This process requires a scalable, cost-effective storage solution that can integrate with cloud-native data processing tools like Apache Spark.
2. Inference & RAG: The fine-tuned model will be used in a customer-facing application that leverages Retrieval-Augmented Generation (RAG). To ensure low-latency responses, the RAG component requires extremely fast lookups from a 10 TB vector database.
The company needs a solution that optimizes both cost and performance for this entire lifecycle.
Which combination of NetApp technologies provides the most appropriate solution for this scenario?

A. Use NetApp E-Series for the data lake and a NetApp ASA system for the vector database.
B. Use NetApp Cloud Volumes ONTAP for the data lake and NetApp StorageGRID for the vector database.
C. Use a single, large NetApp ASA system for both the object data lake and the vector database.
D. Use NetApp StorageGRID for the data lake and a NetApp ASA system for the vector database.

Answer: D

NEW QUESTION # 109
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