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Snowflake SnowPro® Specialty: Gen AI Certification Sample Questions:

1. A developer has successfully created a Cortex Search Service named within knowledge_base. Services based on a large repository of technical product manuals. They now need to query this service to find sections discussing 'troubleshooting network issues' specifically for products tagged as 'ModelX', returning only the 3 most relevant results and including the 'manual_title' and 'section_id' in the output. Which of the following SQL commands correctly performs this query?

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

2. A new data analyst is trying to incorporate sentiment analysis using SNOWFLAKE. CORTEX. SENTIMENT within a Snowflake data pipeline that uses dynamic tables. They execute the following SQL to create a dynamic table for daily sentiment aggregation:

However, this operation fails. Which of the following is the most direct reason for the failure of this specific setup?

A) The TARGET_LAG for dynamic tables must be explicitly set to '1 day' or longer when integrating with Cortex functions.
B) The CORTEX_USER database role was not granted to the analyst's role, preventing the execution of Cortex functions.
C) The warehouse my_analytics_wh is likely not a Snowpark-optimized warehouse, which is a requirement for Cortex functions within dynamic tables.
D) The review_content column, if containing non-English text, would cause the SENTIMENT function to fail outright rather than produce inaccurate results.
E) SNOWFLAKE. CORTEX. SENTIMENT and other Snowflake Cortex functions are currently incompatible with dynamic tables.

3. A Data Scientist has a pre-trained PyCaret model and wants to log it into the Snowflake Model Registry for inference. The model requires specific versions of and 'scipy' , and a configuration file 'my_config.json' needs to be packaged with the model for use during inference. Assuming 'sp_session' is an active Snowpark Session, is an instance of 'PyCaretModel' , and 'train_features' is a Pandas DataFrame for which of the following code snippets correctly logs this custom PyCaret model into the Snowflake Model Registry?

A)

B)

C)

D)

E)

4. A data analytics team is building a Retrieval Augmented Generation (RAG) application to provide contextual answers from a vast repository of internal documents stored in Snowflake. They are evaluating different strategies for generating and retrieving text embeddings to optimize the overall RAG pipeline's performance and relevance. Which of the following statements accurately describe performance considerations related to embedding generation and retrieval in this RAG context? (Select all that apply)

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

5. A financial institution uses Snowflake Cortex Analyst with strict role-based access control (RBAC) on their Snowflake-hosted LLMs. The security team has granted specific 'CORTEX-MODEL-ROLE application roles to different analyst teams, ensuring they only access approved models. A new requirement arises to enable Azure OpenAI GPT models for Cortex Analyst to leverage a specific feature. An administrator proceeds to execute:

Which of the following statements accurately describe the implications of this change?

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

Solutions: