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Network Appliance NS0-901 Exam Syllabus Topics:

SectionWeightObjectives
AI Hardware Architectures18%- NetApp Architectures
  • 1. OVX architectures
  • 2. BasePod
  • 3. SuperPOD
- Networking and Storage
  • 1. Network protocols for AI workloads
  • 2. Storage architectures for AI
- Infrastructure Topologies
  • 1. Data aggregation and compute topologies
AI Lifecycle27%- 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)
- Model Development
  • 1. Model building
  • 2. Inferencing
  • 3. Fine-tuning workflows
- Data Preparation
  • 1. XCP and CopySync
  • 2. Data aggregation and cleansing
  • 3. NetApp BlueXP Classification
- Generative AI Concepts
  • 1. Fine-tuning
  • 2. Hallucinations
  • 3. Retrieval Augmented Generation (RAG)
AI Software Architectures18%- MLOps and LLMOps Ecosystems
  • 1. Understanding the software tools and platforms enabling AI at scale
- 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
AI Common Challenges22%- 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. Optimizing data access and movement
  • 3. Maximizing performance in demanding AI workloads
AI Overview15%- AI Deployment Models
  • 1. Edge
  • 2. Cloud
  • 3. Benefits and risks of each model
  • 4. On-premises
- Machine Learning Fundamentals
  • 1. Understand the relationship between AI, machine learning, and deep learning
  • 2. Describe machine learning benefits
- AI Industry Applications
  • 1. Agents
  • 2. Digital twins
  • 3. Healthcare applications
- AI Convergence with HPC and Analytics
  • 1. Leveraging shared infrastructure for AI, HPC, and analytics
- Training vs. Inferencing vs. Predictions
  • 1. Distinguish between training and inference workloads
- Algorithm Types
  • 1. Unsupervised learning
  • 2. Reinforcement learning
  • 3. Supervised learning

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Network Appliance NetApp Certified AI Expert Exam Sample Questions (Q66-Q71):

NEW QUESTION # 66
An AI architect is designing a storage solution for a new training cluster. The primary workload consists of training large language models, which involves sequential reads of massive datasets.
The key requirement is to maximize GPU utilization by providing the highest possible data throughput. Cost is a secondary concern to performance.
Which NetApp storage system is the most appropriate choice for this workload?

Answer: A


NEW QUESTION # 67
A robotics company is developing a control system for an autonomous warehouse drone. The drone must learn to navigate complex environments to pick up packages. The development team has created a physics-based simulation where the drone can attempt the task millions of times.
The drone receives a positive reward for successfully retrieving a package and a negative penalty for collisions. Which type of machine learning algorithm is being used in this scenario?

Answer: D


NEW QUESTION # 68
An organization wants to provide its data science team with a secure, on-demand method for using a powerful generative AI model with their private, sensitive corporate data. The solution must ensure that the private data is never exposed to the public internet or the public LLM API endpoint.
The architect is designing a solution using BlueXP.
Which two components are essential for building this secure solution? (Choose 2.)

Answer: B,C


NEW QUESTION # 69
A data scientist needs to test a new data normalization technique. To do this, they require an isolated, writable copy of a 50 TB curated simulation dataset that resides on the NetApp ASA system. The operation must be completed as quickly as possible and consume minimal additional storage space. Which NetApp technology is the most appropriate solution for this requirement?

Answer: B


NEW QUESTION # 70
Which of the following applications use AI in the healthcare industry? (Choose two)

Answer: B,C


NEW QUESTION # 71
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