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Snowflake SnowPro® Specialty: Gen AI Certification Sample Questions:

1. A Gen AI specialist is tasked with creating a Snowflake Cortex Search Service to power a Retrieval Augmented Generation (RAG) application for customer support transcripts. The goal is to allow semantic search over the 'transcript_text' column, filter results by 'region' and , and leverage a multilingual embedding model for high-quality results. The service should be created in the 'cortex_search_db.serviceS schema and use as the warehouse. Which of the following SQL commands correctly creates such a Cortex Search Service, assuming 'support_transcripts' is the source table and change tracking is enabled?

A)

B)

C)

D)

E)

2. A data application developer is tasked with building a multi-turn conversational AI application using Streamlit in Snowflake (SiS) that leverages the COMPLETE (SNOWFLAKE. CORTEX) LLM function. To ensure the conversation flows naturally and the LLM maintains context from previous interactions, which of the following is the most appropriate method for handling and passing the conversation history?

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

3. A Data Engineer is responsible for deploying machine learning models using Snowpark Container Services. They need to ensure that a specific role, model_deployer_role, has the appropriate permissions to create a Snowpark Container Service that uses an image from an existing image repository named my_inferenc_ images. Which of the following SQL commands grant the necessary privileges 'on the image repository' for this purpose?

A)

B)

C)

D)

E)

4. A legal department uses Snowflake to manage and review large volumes of contracts. They need to automate the process of finding specific pieces of information, such as the effective_date or involved_parties, from these unstructured contract texts. They are considering using SNOWFLAKE. CORTEX. EXTRACT_ANSWER. Which characteristic correctly describes the primary intent or behavior of SNOWFLAKE. CORTEX. EXTRACT_ANSWER, distinguishing it from other LLM functions?

A) It focuses on identifying and returning a direct answer to a specific question contained within the provided source document.
B) It is primarily designed to generate entirely new text based on a given prompt, much like a conversational AI.
C) It classifies an input text into one of several predefined categories provided by the user.
D) It evaluates a text and returns a numeric score indicating the overall positive or negative sentiment.
E) It transforms an input document into a summarized version, reducing its length while preserving key information.

5. An enterprise is deploying a new RAG application using Snowflake Cortex Search on a large dataset of customer support tickets. The operations team is concerned about managing compute costs and ensuring efficient index refreshes for the Cortex Search Service, which needs to be updated hourly. Which of the following considerations and configurations are relevant for optimizing cost and performance of the Cortex Search Service in this scenario?

A) The

B) CHANGE_TRACKING
C) The primary cost driver for Cortex Search is the number of search queries executed against the service, with the volume of indexed data (GB/month) having a minimal impact on overall billing.
D) For optimal performance and cost efficiency, Snowflake recommends using a dedicated warehouse of size no larger than MEDIUM for each Cortex Search Service.
E) For embedding text, selecting a model like

Solutions: