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Network Appliance NS0-901 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: AI Hardware Architectures | 18% | - NetApp Architectures
|
| Topic 2: AI Software Architectures | 18% | - Development Tools
|
| Topic 3: AI Overview | 15% | - Machine Learning Fundamentals
|
| Topic 4: AI Lifecycle | 27% | - Model Development
|
| Topic 5: AI Common Challenges | 22% | - Traceability and Optimization
|
Network Appliance NetApp Certified AI Expert Sample Questions:
1. 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?
A) NetApp FabricPool
B) NetApp FlexClone
C) NetApp XCP
D) NetApp SnapMirror
2. 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?
A) Supervised learning
B) Generative learning
C) Reinforcement learning
D) Unsupervised learning
3. What is the primary role of NetApp Trident in a Kubernetes environment designed for AI workloads?
A) To function as a container runtime interface for executing AI models.
B) To act as a dynamic storage orchestrator, provisioning persistent storage from NetApp backends on- demand for containerized applications.
C) To directly accelerate GPU computations using specialized drivers.
D) To provide a web-based IDE, like Jupyter, for data scientists to develop models.
4. 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?
A) NetApp StorageGRID
B) NetApp E-Series
C) NetApp ASA (All-SAN Array)
D) NetApp C-Series
5. An AI architect is designing a solution for a legal firm. The primary goal is to allow lawyers to ask natural language questions about case law stored in a private, 50 TB document repository.
The key project constraints are as follows:
Project_Goal: Answer questions using proprietary, real-time legal documents.
Constraint_1: Must not alter the foundational LLM's weights due to compliance.
Constraint_2: Case law database is updated daily with new rulings.
Constraint_3: All generated answers must be traceable to a source document.
Which technology should the architect choose as the core of this solution?
A) A new LLM trained from scratch on the legal documents.
B) A Retrieval-Augmented Generation (RAG) architecture.
C) A fine-tuning pipeline to update the LLM daily.
D) A predictive AI model to classify legal documents.
Solutions:
| Question # 1 Answer: B | Question # 2 Answer: C | Question # 3 Answer: B | Question # 4 Answer: C | Question # 5 Answer: B |







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