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Network Appliance NS0-901 Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: AI Software Architectures	18%	- MLOps and LLMOps Ecosystems 1. Understanding the software tools and platforms enabling AI at scale - Scaling and Orchestration 1. Leveraging BlueXP software tools 2. Scaling AI workloads with Kubernetes - Development Tools 1. Jupyter notebooks vs. pipelines 2. NetApp DataOps Toolkit
Topic 2: AI Common Challenges	22%	- Resource Management 1. Sizing storage and compute resources effectively 2. Controlling costs and securing storage - Traceability and Optimization 1. Optimizing data access and movement 2. Ensuring traceability for code, data, and models 3. Maximizing performance in demanding AI workloads
Topic 3: AI Hardware Architectures	18%	- Infrastructure Topologies 1. Data aggregation and compute topologies - NetApp Architectures 1. SuperPOD 2. OVX architectures 3. BasePod - Networking and Storage 1. Network protocols for AI workloads 2. Storage architectures for AI
Topic 4: AI Overview	15%	- Machine Learning Fundamentals 1. Describe machine learning benefits 2. Understand the relationship between AI, machine learning, and deep learning - Training vs. Inferencing vs. Predictions 1. Distinguish between training and inference workloads - Algorithm Types 1. Supervised learning 2. Unsupervised learning 3. Reinforcement learning - AI Deployment Models 1. Edge 2. Cloud 3. On-premises 4. Benefits and risks of each model - AI Convergence with HPC and Analytics 1. Leveraging shared infrastructure for AI, HPC, and analytics - AI Industry Applications 1. Healthcare applications 2. Agents 3. Digital twins
Topic 5: AI Lifecycle	27%	- Generative AI Concepts 1. Fine-tuning 2. Retrieval Augmented Generation (RAG) 3. Hallucinations - Model Development 1. Model building 2. Inferencing 3. Fine-tuning workflows - 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) - Data Preparation 1. XCP and CopySync 2. Data aggregation and cleansing 3. NetApp BlueXP Classification

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Network Appliance NetApp Certified AI Expert Exam Sample Questions (Q30-Q35):

A. Project A requires only a large amount of data, while Project B requires only a large amount of code.
B. Project A is a model building task and requires a significantly larger and more powerful compute and storage infrastructure than Project B.
C. Project B is a fine-tuning task, which leverages an existing model and requires less data and compute resources than building a model from scratch.
D. Both projects are examples of fine-tuning and have similar infrastructure needs.
E. Both projects should use NetApp StorageGRID as the primary storage for training to ensure low latency.

Answer: B,C

NEW QUESTION # 31
An AI architect needs to design a complete, end-to-end data pipeline for a new generative AI application at a financial services firm. The application will allow internal analysts to query a massive, 500 TB archive of historical market data and reports to generate summaries. The firm has the following environment and requirements:
Data_Sources: A mix of on-premises ONTAP filers and StorageGRID S3 buckets.
Requirement_1: All queries must be answered using only the private data archive.
Requirement_2: All generated summaries must provide citations to the source reports.
Requirement_3: All data containing client PII must be identified and excluded from the LLM context.
Requirement_4: The solution must be cost-effective for the large, mostly-read data archive.
Which set of actions and technologies constitutes the most robust and compliant solution?
(Select all that apply.)

A. Fine-tune a foundation model on the entire 500 TB dataset to ensure it understands the financial context.
B. Use SnapMirror to replicate the StorageGRID data lake to a high-performance NetApp ASA system for faster query performance.
C. During the RAG retrieval step, filter out any documents tagged as containing PII by BlueXP classification before sending them to the LLM.
D. Implement a Retrieval-Augmented Generation (RAG) architecture to meet the requirements for private data usage and source citation.
E. Deploy BlueXP classification to scan the entire StorageGRID data lake to identify and tag all files containing PII.
F. Use NetApp XCP to perform a one-time migration of all data from the ONTAP filers to the StorageGRID data lake.

Answer: C,D,E,F

NEW QUESTION # 32
A new team of external auditors requires read-only access to the raw financial product documentation stored in the StorageGRID data lake. The data is in a bucket named 'prod-docs'.
The security team must ensure the auditors can list and read objects but cannot write, delete, or modify any data. Which is the most appropriate method to grant this specific access?

A. Create a new StorageGRID tenant account for the auditors with full S3 access.
B. Provide the auditors with the root access keys for the StorageGRID system.
C. Configure an NFS export policy on the 'prod-docs' bucket and provide the auditors with the mount path.
D. Create a new group and user within StorageGRID, and attach an S3 group policy that explicitly allows only 's3:GetObject' and 's3:ListBucket' actions on the 'prod-docs' bucket.

Answer: D

NEW QUESTION # 33
Which storage protocols are commonly used for handling large-scale AI data? (Choose two)

A. File-based systems
B. POSIX-based file systems
C. Parallel file systems
D. Object-based storage

Answer: C,D

NEW QUESTION # 34
The Chief Information Security Officer (CISO) is concerned about the risk of a ransomware attack encrypting the critical vector database hosted on the NetApp AFF A-Series. The CISO wants a solution that can proactively detect and block a live attack in real-time, not just recover from a backup after the fact.
Which NetApp security feature should the architect enable on the vector database volume to meet this requirement?

A. Multi-Admin Verification (MAV)
B. Autonomous Ransomware Protection (ARP)
C. NetApp Volume Encryption (NVE)
D. NetApp SnapLock (Compliance Mode)

Answer: B

NEW QUESTION # 35
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