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Network Appliance NS0-901 Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: AI Common Challenges	22%	- Resource Management 1. Controlling costs and securing storage 2. Sizing storage and compute resources effectively - Traceability and Optimization 1. Maximizing performance in demanding AI workloads 2. Ensuring traceability for code, data, and models 3. Optimizing data access and movement
Topic 2: AI Lifecycle	27%	- Predictive AI vs. Generative AI 1. Distinction between predictive and generative AI 2. Impact of generative content (text, images, video, decision-making) 3. Large Language Models (LLMs) - Model Development 1. Fine-tuning workflows 2. Model building 3. Inferencing - Data Preparation 1. NetApp BlueXP Classification 2. XCP and CopySync 3. Data aggregation and cleansing - Generative AI Concepts 1. Fine-tuning 2. Retrieval Augmented Generation (RAG) 3. Hallucinations
Topic 3: AI Hardware Architectures	18%	- NetApp Architectures 1. OVX architectures 2. BasePod 3. SuperPOD - Infrastructure Topologies 1. Data aggregation and compute topologies - Networking and Storage 1. Storage architectures for AI 2. Network protocols for AI workloads
Topic 4: AI Overview	15%	- AI Industry Applications 1. Digital twins 2. Healthcare applications 3. Agents - AI Deployment Models 1. Cloud 2. Edge 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 - 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. Unsupervised learning 2. Reinforcement learning 3. Supervised learning
Topic 5: AI Software Architectures	18%	- Development Tools 1. Jupyter notebooks vs. pipelines 2. NetApp DataOps Toolkit - Scaling and Orchestration 1. Leveraging BlueXP software tools 2. Scaling AI workloads with Kubernetes - MLOps and LLMOps Ecosystems 1. Understanding the software tools and platforms enabling AI at scale

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Network Appliance NetApp Certified AI Expert Exam Sample Questions (Q73-Q78):

NEW QUESTION # 73
Given the company's goal of combining physics-based simulations with AI-driven analytics on a shared data foundation, which industry trend does this project best represent?

A. The separation of AI and HPC into dedicated, air-gapped environments.
B. The replacement of all physical testing with digital simulations.
C. The convergence of AI, High-Performance Computing (HPC), and analytics on a unified data infrastructure.
D. The exclusive use of public cloud resources for all computational tasks.

Answer: C

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

Answer: A,E

NEW QUESTION # 75
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. Configure an NFS export policy on the 'prod-docs' bucket and provide the auditors with the mount path.
B. Create a new StorageGRID tenant account for the auditors with full S3 access.
C. 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.
D. Provide the auditors with the root access keys for the StorageGRID system.

Answer: C

NEW QUESTION # 76
The firm's CFO is concerned about the rising costs of the on-premises AI infrastructure. A storage utilization report shows that of the 200 TB of data on the high-performance AFF A-Series, 150 TB consists of inactive, older versions of product documents that are rarely accessed but must be kept online for regulatory reasons.
The current storage landscape is:
- Performance Tier: NetApp AFF A-Series (200 TB used)
- Capacity Tier: NetApp StorageGRID (1.5 PB used)
What is the most effective and automated solution to reduce the storage cost of the performance tier without impacting data accessibility?

A. Use NetApp SnapMirror to replicate the entire 200 TB volume to the StorageGRID system and then delete the source.
B. Purchase an additional, larger AFF A-Series system to gain better storage efficiency through deduplication.
C. Implement NetApp FabricPool to automatically tier the inactive data blocks from the AFF A-Series to the StorageGRID system.
D. Manually identify and delete the 150 TB of inactive data from the AFF A-Series.

Answer: C

NEW QUESTION # 77
A national research laboratory is investing in a turnkey AI infrastructure solution. Their primary goal is to eliminate the complexity and risk of designing and integrating the compute, network, and storage components themselves. The solution must be pre-validated by the vendors to deliver predictable, linear performance as they scale from one to multiple compute nodes. Which two options represent this type of pre-validated, converged infrastructure solution for AI? (Choose two)

A. NetApp AIPod, which integrates NVIDIA DGX servers with NetApp storage and networking.
B. A custom-built server rack with components sourced from various different vendors.
C. A Cisco and NetApp FlexPod for AI solution.
D. A public cloud provider's general-purpose virtual machine instances.
E. A single NetApp FAS system connected directly to a single server.

Answer: A,C

NEW QUESTION # 78
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