SnowPro® Specialty: Gen AI Certification Exam (GES-C01) Free Practice Test

Question 1

A data scientist fine-tuned a mistral-lb model in Snowflake for a specific customer support response generation task, naming it my_custom_responder_model. They now want to make this model available for AI_COMPLETE calls in production, ensuring proper access control and regional availability. Which of the following statements is true regarding the deployment and management of this fine-tuned model in Snowflake?

A. Option E

B. Option D

C. Option C

D. Option A

E. Option B

Correct Answer: C

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Question 2

A data analyst is using Snowflake Copilot in Snowsight to generate SQL queries for a new dataset containing customer PII. Which of the following statements accurately describes how Snowflake Copilot operates with respect to data access, governance, and model interaction?

A. Snowflake Copilot is powered by a fine-tuned model that runs securely inside Snowflake Cortex, leveraging only database/schema/table/column names and data types, ensuring data remains within Snowflake's governance boundary and respects RBAC.

B. To protect sensitive information, Snowflake Copilot transmits sampled PII data to an external LLM for schema understanding before generating SQL.

C. Snowflake Copilot directly accesses and processes the raw data within customer tables to understand its content and generate SQL.

D. Snowflake Copilot requires explicit column-level grants for direct data access, similar to how a human analyst would query specific data points.

E. While Snowflake Copilot generates SQL based on metadata, the generated SQL queries are executed in an isolated environment that does not respect existing Snowflake RBAC policies.

Correct Answer: A

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Question 3

A data processing team is using Snowflake Document AI to extract data from incoming supplier invoices. They observe that many documents are failing to process, and successful extractions are taking longer than expected, leading to increased costs. Upon investigation, they find error messages such as

. Additionally, their 'X-LARGE virtual warehouse is constantly active, contributing to higher-than-anticipated bills. Which two of the following actions are essential steps to troubleshoot and address the root causes of these processing errors and optimize their Document AI pipeline?

A. Redefine extraction questions to be more generic and encompassing, reducing the number of distinct questions needed per document.

B. Scale down the virtual warehouse to 'X-SMALC or 'SMALL' size, as larger warehouses do not increase Document AI query processing speed and incur unnecessary costs.

C. Configure the internal stage used for storing invoices with 'ENCRYPTION = (TYPE = 'SNOWFLAKE_SSE'Y.

D. Increase the 'max_tokenS parameter within the ' !PREDICT' function options to accommodate longer document responses from the model.

E. Implement a pre-processing step to split documents exceeding 125 pages or 50 MB into smaller, compliant files before loading to the stage.

Correct Answer: C,E

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Question 4

A compliance officer is reviewing the usage of Snowflake Cortex LLM functions and the Cortex REST API within their organization, specifically focusing on the implementation and impact of Cortex Guard. They observe several instances where 'guardrails' were enabled. Which of the following statements accurately describe the behavior and cost considerations of Cortex Guard when integrated with Snowflake Cortex LLM functions or the Cortex REST API?

A. Cortex Guard can be configured with a custom message using the argument in the options object for both 'COMPLETE SQL function and the Cortex REST API.

B. The underlying model for Cortex Guard is Meta's Llama Guard 3, and its processing costs are separate from the primary LLM inference costs.

C. Cortex Guard operates by evaluating responses after the LLM has fully generated its content, and it incurs additional compute cost for both input and output tokens during its processing.

D. When Cortex Guard is enabled and a response is deemed unsafe, the LLM-generated output is replaced with a predefined message, and only the input tokens for Cortex Guard processing ('guard_tokens') are billed, not the potentially unsafe completion tokens.

E. Cortex Guard is inherently part of all Cortex LLM functions and does not require explicit enablement via 'guardrails: TRUE for SQL functions or the REST API.

Correct Answer: A,B,D

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Question 5

An ML engineer is designing a Cortex Agent to provide highly accurate and contextualized responses. They intend for the agent to use state-of-the-art LLMs for orchestration and to maintain a specific brand tone in its outputs. Considering the available models and configurations for Cortex Agents, which statement is true?

A. Cortex Agents are restricted to using only Snowflake Arctic models for orchestration, due to security and governance requirements, and must operate in the account's default region.

B. The agent's 'Planning' component is specifically responsible for evaluating results after each tool use and deciding the subsequent steps in the query resolution process, acting as a feedback loop.

C. To ensure the agent's responses adhere to a desired brand and tone, 'Response instructions' can be configured, which guide the agent's output style and persona.

D. When an agent utilizes an LLM for orchestration, the system ensures that cross-region inference is automatically enabled without any latency implications, making region selection irrelevant.

E. Cortex Agents primarily interact with data through the Snowflake Model Registry API to retrieve and update fine-tuned model parameters during their iterative planning phase.

Correct Answer: C

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Question 6

database role. Which of the following 'privileges directly related to the virtual warehouse or task execution' are required for the process invoices_task' to successfully execute the Document AI '!PREDICT' method? (Select ALL that apply.)

A.

B.

C.

D.

E.

Correct Answer: A,C,D

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Question 7

A data engineering team needs to implement a highly accurate, low-latency solution for classifying specialized technical documents into 50 distinct categories. They are considering fine-tuning a Large Language Model (LLM) within Snowflake Cortex for this task. Which of the following considerations are critical for optimizing the fine-tuned model's performance and minimizing inference latency for production use? (Select all that apply)

A. Option E

B. Option D

C. Option C

D. Option A

E. Option B

Correct Answer: D,E

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Question 8

A data engineering manager needs to audit Cortex LLM function costs to identify specific SQL queries that are unexpectedly high in token consumption for the 'llama3.1-8b' model. They require granular analysis of prompt, completion, and guardrail token usage for these queries. Which of the following Snowflake methods or views would provide the necessary insights?

A. Option E

B. Option D

C. Option C

D. Option A

E. Option B

Correct Answer: B,E

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Snowflake SnowPro® Specialty: Gen AI Certification (GES-C01) Free Practice Test