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Network Appliance NetApp Certified AI Expert Sample Questions:

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

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

3. The firm wants to extend the "Advisor Assistant" to include a new batch processing feature. Every night, the system must analyze every client portfolio against a set of 50 different risk models and generate a compliance report. This is a highly parallel, read-intensive workload. The architect must design a data workflow that is efficient and does not impact the production chatbot environment. Which sequence of actions and technologies provides the most effective solution?

A) Use NetApp SnapMirror to replicate the portfolio database volume to the DR site, and run the analysis jobs there.
B) Create a full physical copy of the client portfolio database to a separate volume, mount it to the compute nodes, and run the analysis.
C) Create a NetApp Snapshot of the portfolio database volume, create a FlexClone from that snapshot, mount the FlexClone to the analysis pods, and run the batch job.
D) Run the analysis job directly against the production portfolio database during off-peak hours.

4. Which of the following applications use AI in the healthcare industry? (Choose two)

A) Managing hospital supply chains
B) Automating financial reporting
C) Diagnosing diseases
D) Predicting patient outcomes

5. Which of the following are typical requirements for inferencing in AI models? (Choose two)

A) Cloud-based inference only
B) Pre-trained models
C) Extensive training data
D) Loading the model into memory

Solutions: