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Network Appliance NS0-901 Exam Syllabus Topics:

SectionObjectives
Topic 1: AI Lifecycle and Deployment- End-to-end AI lifecycle
  • 1. Data ingestion and preparation
    • 2. Model training and validation
      • 3. Model deployment and monitoring
        - Operational challenges
        • 1. Scalability and performance optimization
          • 2. Data governance and management
            Topic 2: AI Infrastructure and NetApp Solutions- AI-ready data infrastructure
            • 1. High-performance storage for AI workloads
              • 2. Data pipeline optimization for AI/ML workloads
                - Converged workloads
                • 1. AI, HPC, and analytics convergence
                  • 2. Shared infrastructure design considerations
                    Topic 3: Industry Use Cases- AI applications across industries
                    • 1. Healthcare AI
                      • 2. Autonomous systems and agents
                        • 3. Digital twins
                          Topic 4: AI and Machine Learning Fundamentals- Algorithm types
                          • 1. Supervised learning
                            • 2. Unsupervised learning
                              • 3. Reinforcement learning
                                - AI, ML, DL concepts
                                • 1. Training, inference, and prediction workflows
                                  • 2. Differences between AI, machine learning, and deep learning

                                    Network Appliance NetApp Certified AI Expert Sample Questions:

                                    1. Which AI technology is used to generate new, never-before-seen content such as images or text?

                                    A) Reinforcement AI
                                    B) Generative AI
                                    C) Predictive AI
                                    D) Supervised AI


                                    2. A junior administrator is attempting to delete an old, unused Snapshot copy from a production volume to reclaim space but receives an error. The administrator is certain they are using the correct command and have the appropriate 'vsadmin' role.
                                    The command and error are shown below:
                                    cluster-1::> volume snapshot delete -vserver svm_prod -volume app_data -snapshot nightly.2025- 06-15_0015 Error: command failed: This operation is not permitted. Deletion of Snapshot copy "nightly.2025-
                                    06-15_0015" on volume "app_data" in Vserver "svm_prod" requires approval.
                                    Use the "security multi-admin-verify approval show" command to view pending approvals.
                                    What is the most likely reason the administrator cannot delete the Snapshot?

                                    A) The Snapshot is locked by a SnapMirror relationship.
                                    B) The volume is protected by SnapLock, and the Snapshot has not reached its expiry date.
                                    C) Multi-Admin Verification (MAV) is enabled, and the destructive operation requires approval from another designated administrator.
                                    D) The 'vsadmin' role does not have permission to delete Snapshots.


                                    3. 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 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.
                                    B) Configure an NFS export policy on the 'prod-docs' bucket and provide the auditors with the mount path.
                                    C) Provide the auditors with the root access keys for the StorageGRID system.
                                    D) Create a new StorageGRID tenant account for the auditors with full S3 access.


                                    4. A company is running its AI training workloads on a NetApp AFF A-Series system. To manage costs, they want to automatically move inactive training datasets and older model checkpoints from the high- performance all-flash tier to a lower-cost object storage tier, such as an on- premises StorageGRID or a public cloud bucket. The process must be transparent to the data scientists and not require changes to their scripts or file paths.
                                    Which two NetApp technologies should be combined to achieve this goal? (Choose 2.)

                                    A) NetApp FabricPool
                                    B) NetApp SnapMirror
                                    C) NetApp FlexCache
                                    D) NetApp StorageGRID
                                    E) NetApp XCP


                                    5. An enterprise is planning a generative AI solution to power its internal support chatbot. The architect must choose between a RAG-based approach and fine-tuning a base model. The project stakeholders have provided a list of prioritized requirements.
                                    | Requirement | Priority | Details
                                    |
                                    | | -- | |
                                    | Factual Accuracy | Critical | Must use the latest product documentation, updated daily.
                                    | | Brand Voice & Persona | High | Must respond in the company's specific, formal tone.
                                    | | Development Cost | High | Limited budget for GPU compute hours for model training.
                                    |
                                    | Data Traceability | Critical | Must be able to cite the exact source document for each answer.
                                    |
                                    Which two recommendations should the architect make to best satisfy these requirements?
                                    (Choose 2.)

                                    A) Recommend training a new LLM from scratch to ensure both brand voice and factual accuracy are built-in.
                                    B) Prioritize a RAG architecture to meet the critical requirements for factual accuracy and data traceability.
                                    C) Propose a hybrid approach where a base model is first lightly fine-tuned for persona, then used within a RAG system for factual grounding.
                                    D) Prioritize fine-tuning to embed the company's brand voice and persona into the model.
                                    E) Use RAG exclusively, as prompt engineering alone can fully replicate a specific brand voice and persona.


                                    Solutions:

                                    Question # 1
                                    Answer: B
                                    Question # 2
                                    Answer: C
                                    Question # 3
                                    Answer: A
                                    Question # 4
                                    Answer: A,D
                                    Question # 5
                                    Answer: B,C

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