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Snowflake SnowPro® Specialty: Gen AI Certification Sample Questions:

1. A large e-commerce company plans to implement real-time sentiment analysis on millions of incoming customer reviews using SNOWFLAKE. CORTEX. SENTIMENT. They are concerned about managing costs and ensuring efficient processing. Which of the following statements about cost considerations and performance optimizations for SNOWFLAKE. CORTEX. SENTIMENT are true?
(Select all that apply)

A) The newer AI_SENTIMENT function is a free, serverless alternative to SNOWFLAKE. CORTEX. SENTIMENT, offering cost savings for high-volume scenarios.
B) Snowflake recommends using a smaller warehouse (no larger than MEDIUM), as larger warehouses do not increase performance for SENTIMENT function calls.
C) The fixed billing rate for the SENTIMENT function is 0.08 Credits per one million input tokens processed.
D) Billing for SNOWFLAKE. CORTEX. SENTIMENT is primarily based on the number of output tokens generated in the response.
E) The actual number of tokens processed and billed for a SENTIMENT call is typically higher than the raw input text length, due to an internal prompt added by the function.

2. An organization is implementing a two-tier LLM access control strategy in Snowflake. First, common models like 'mistral-7b' and 'llama3.1-8b' need to be broadly accessible to all users granted the 'SNOWFLAKE-CORTEX USER database role. Second, a specialized data science team, using the ANALYST ROLE', requires exclusive access to the higher-capability 'claude-3-5- sonnet' model, which should NOT be generally available through the broad access mechanism. Which set of SQL commands, executed by the 'ACCOUNTADMIN" role, correctly establishes this access control strategy?

A)

B)

C)

D)

E)

3. A data scientist is tasked with improving the accuracy of an LLM-powered chatbot that answers user questions based on internal company documents stored in Snowflake. They decide to implement a Retrieval Augmented Generation (RAG) architecture using Snowflake Cortex Search. Which of the following statements correctly describe the features and considerations when leveraging Snowflake Cortex Search for this RAG application?

A) Cortex Search automatically handles text chunking and embedding generation for the source data, eliminating the need for manual ETL processes for these steps.
B) To create a Cortex Search Service, one must explicitly specify an embedding model and manually manage its underlying infrastructure, similar to deploying a custom model via Snowpark Container Services.
C) Enabling change tracking on the source table for the Cortex Search Service is optional; the service will still refresh automatically even if change tracking is disabled.
D) The
E) For optimal search results with Cortex Search, source text should be pre-split into chunks of no more than 512 tokens, even when using models with larger context windows like

4. A software development team is building a conversational AI application within Snowflake, aiming to provide a dynamic and stateful chat experience for users. The application needs to handle follow-up questions while maintaining context, provide responses with a degree of creative variation, and actively filter out any potentially harmful content. The team utilizes the SNOWFLAKE. CORTEX. COMPLETE (or AI_COMPLETE) function.

A)

B)

C)

D)

5. A software development team is building a conversational AI application within Snowflake, aiming to provide a dynamic and stateful chat experience for users. The application needs to handle follow-up questions while maintaining context, provide responses with a degree of creative variation, and actively filter out any potentially harmful content. The team utilizes the SNOWFLAKE. CORTEX. COMPLETE (or AI_COMPLETE) function.

A)

B)

C)

D)

E)

Solutions: