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Snowflake SnowPro® Specialty: Gen AI Certification Sample Questions:

1. A financial analyst wants to build a generative AI application in Snowflake that can answer complex queries by integrating financial reports (unstructured data in stages) and transaction records (structured data in tables). They decide to use Snowflake Cortex Agents. Which of the following statements accurately describe the capabilities and operational aspects of Cortex Agents in this scenario?
(Select all that apply)

A) Cortex Agents are designed to orchestrate tasks by planning steps, utilising tools like Cortex Analyst for structured data and Cortex Search for unstructured data, and generating comprehensive responses.
B) For monitoring agent interactions and performance on the client application, the TruLens Python packages (

C) The primary compute cost for Cortex Agents is based on the number of tokens processed during the planning and reflection phases, with an additional per- message charge for each tool invocation.
D) When a user asks an ambiguous question, Cortex Agents utilise an 'Explore options' component to consider different permutations and disambiguate the query for improved accuracy.
E) To provide the Agent with custom logic for specific data transformations not covered by standard tools, stored procedures or user-defined functions (UDFs) can be implemented as custom tools.

2. A data scientist is implementing a Retrieval Augmented Generation (RAG) system in Snowflake for a legal document repository. They need to convert legal document chunks into vector embeddings and efficiently find the most relevant document chunks based on a user's query. Which of the following statements accurately describe the process and best practices for creating and using these vector embeddings with Snowflake Cortex LLM functions?

A) Option A
B) Option C
C) Option D
D) Option E
E) Option B

3. An ML engineer is developing a RAG application in Python and wants to use the TruLens SDK to trace the distinct phases of its execution, specifically the context retrieval and answer generation steps. They aim to clearly differentiate the tracing of the function responsible for retrieving context.

A)

B)

C)

D)

E)

4. A Snowflake developer, named ANALYST USER, is tasked with creating a Streamlit in Snowflake (SiS) application that will utilize both SNOWFLAKE. CORTEX. COMPLETE for generating responses and SNOWFLAKE. CORTEX.CLASSIFY_TEXT for categorizing user input. To ensure the role used by ANALYST USER has the necessary permissions for executing these Cortex LLM functions and operating within a specified database and schema, which of the following database roles or privileges must be granted? (Select all that apply.)

A)

B) The USAGE privilege on the database and schema where the Streamlit application runs and potentially stores related data.
C)

D)

E)

5. A security auditor needs to access and analyze logs generated by Snowflake AI Observability for compliance auditing and to track the activity of generative AI applications. They need to understand how to reliably query this data and its temporal characteristics within Snowflake. Which of the following statements accurately describes the access and characteristics of this logged data?

A) The logs are automatically purged after 7 days of being recorded, requiring a separate process for long-term data retention.
B) Access to these detailed event tables is implicitly granted to roles holding the SNOWFLAKE. CORTEX_USER database role and the AI_OBSERVABILITY_EVENTS_LOOKUP application role.
C) Logged data from AI Observability's event tables becomes visible within a small latency, typically 1-2 minutes, after a request is made.
D) Detailed request and response bodies, along with the generated SQL, are stored and can be directly queried using standard SQL.
E) Logs are exclusively available for analysis through pre-built dashboards in Snowsight and cannot be accessed via direct SQL queries.

Solutions: