SnowPro® Specialty: Gen AI Certification Exam

Question 1

A security-conscious data scientist in an Azure East US 2 (Virginia) account wants to fine-tune a mistral -7b model for a specific text summarization task and then deploy it for real-time inference using the Cortex REST API. The mistral-7b base model is natively available for fine-tuning in Azure East US 2 (Virginia). For subsequent inference using the fine-tuned model, they need to understand the regional and cross-region inference considerations. Which of the following statements are correct?

A. Option E

B. Option D

C. Option B

D. Option A

E. Option C

Correct Answer: A,B,C,D

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Question 2

A machine learning team is leveraging the Snowflake Model Registry to manage diverse models, including a custom Python utility for data preprocessing that they wish to make available as a model method. Which of the following statements accurately describe capabilities or considerations when logging models and their associated artifacts and methods in the Model Registry?

A. Option E

B. Option D

C. Option B

D. Option A

E. Option C

Correct Answer: A,B,C,E

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Question 3

A data engineering team is onboarding a new client whose workflow involves extracting critical financial data from thousands of daily scanned PDF receipts. They decide to use Snowflake Document AI and store all incoming PDFs in an internal stage name. After deploying their pipeline, they observe intermittent failures and varying error messages in the output, specifically:

Which two of the following actions are most likely required to resolve these processing errors?

A. Ensure the internal stage is configured with 'ENCRYPTION = (TYPE = 'SNOWFLAKE_SSE')'.

B. Change the virtual warehouse size from an X-Small to a Large to improve Document AI processing speed.

C. Increase the 'max_tokens' parameter within the ' !PREDICT function options to accommodate longer document processing.

D. Grant the 'SNOWFLAKCORTEX_USER database role to the role executing the '!PREDICT function.

E. Split any PDF documents exceeding 125 pages into smaller, compliant files, or reject them if splitting is not feasible.

Correct Answer: A,E

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Question 4

A business analyst is using a Cortex Analyst-powered conversational application to query structured data in Snowflake. They initially ask, 'What was the total profit from California last quarter?' and then follow up with, 'What about New York?' The application successfully provides accurate answers to both questions. Which of the following statements explain how Cortex Analyst supports this multi-turn conversational experience and maintains accuracy? (Select all that apply)

A. For multi-turn conversations, Cortex Analyst primarily relies on semantic search over sample values defined in the semantic model to infer context and generate SQL, making explicit conversation history management unnecessary.

B. Cortex Analyst stores the full, verbatim history of all previous user prompts and LLM responses, which are then passed to every subsequent LLM call to ensure complete context retention without any summarization.

C. The accuracy of the SQL queries generated by Cortex Analyst for follow-up questions is significantly enhanced by its integration with a Verified Query Repository (VQR), which stores pre-verified natural language questions and their corresponding SQL queries.

D. The semantic model YAML file, which defines logical tables, dimensions, and measures, is crucial for Cortex Analyst to bridge the gap between business terminology and underlying technical schema, thereby improving text-to-SQL conversion accuracy for both initial and follow-up queries.

E. To handle follow-up questions, Cortex Analyst leverages an internal LLM summarization agent (e.g., Llama 3.1 70B) to reframe the current-turn question by retrieving context from the conversation history, rather than simply passing the entire history.

Correct Answer: C,D,E

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Question 5

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 E

B. Option D

C. Option B

D. Option A

E. Option C

Correct Answer: D,E

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Question 6

A Gen AI Specialist is setting up Snowpark Container Services (SPCS) to host a custom open-source LLM. They need to understand the fundamental nature and constraints of image repositories within Snowflake. Which of the following statements accurately describe image repositories in Snowflake's Snowpark Container Services?

A. Image repositories are primarily used for storing pre-trained Snowflake ML models and do not support custom third-party container images.

B. An image repository in Snowflake is an OCIv2 compliant service used exclusively for storing Docker images, not other OCI-compliant container images.

C. Image repositories are storage units within an image registry service, and they are used to store OCI-compliant container images.

D. Dropping individual images from a repository is supported, allowing for granular management of stored container images.

E. The maximum compressed layer size for an image registry is consistent across all cloud providers and regions, typically 160 GiB.

Correct Answer: C

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Question 7

An organization relies on Snowflake Cortex LLM functions and has established a robust model governance policy using the 'CORTEX MODELS_ALLOWLIST parameter. A developer is integrating 'TRY COMPLETE into an application for processing various text inputs. Which of the following statements are correct regarding 'TRY COMPLETE and model access controls?

A. To provide a stateful conversational experience with 'TRY_COMPLETE, the function automatically retains context from previous calls within the same session.

B. The 'TRY_COMPLETE function can return a 'NULL ' value if the underlying LLM experiences a temporary internal processing error during response generation, allowing the query execution to continue without halting.

C. The parameter primarily governs access for models invoked by their plain names with but 'TRY COMPLETE can still access models if the user has been granted appropriate RBAC on a fully-qualified model object.

D. If 'TRY_COMPLETE fails to perform its operation and returns ' NULL ' , the tokens that would have been processed for that specific call are not billed, ensuring cost efficiency for failed operations.

E. if a If a model specified in 'TRY_COMPLETE is not allowed by the and no RBAC grant exists for it, the 'TRY_COMPLETE function will automatically return 'NULL' to prevent a hard error.

Correct Answer: B,C,D

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Question 8

An ML Engineer has developed a custom PyTorch model for GPU-powered inference and successfully built an OCI-compliant image locally. They now need to push this image to a Snowflake image repository and configure a Snowpark Container Service to use it. The Snowflake account identifier is my org_name_my_account_id_prod. Which set of commands correctly demonstrates tagging the local image and pushing it to the repository?

A. Option E

B. Option D

C. Option B

D. Option A

E. Option C

Correct Answer: C,D

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Question 9

A SnowPro-certified engineer is tasked with setting up AI Observability for a new generative AI application built using Snowpark Python. The application relies on external Python libraries (e.g., TruLens SDK components) and will process sensitive financial documents. Which of the following steps are crucial for the successful setup and secure operation of AI Observability within Snowflake, given these considerations?

A. Option E

B. Option D

C. Option B

D. Option A

E. Option C

Correct Answer: C,D,E

Question 10

An operations team at a company is implementing a robust governance framework to monitor and optimize the costs associated with their Snowflake Cortex LLM function usage. They need to identify which functions are driving the highest token consumption and overall credit usage to pinpoint areas for cost reduction. Which of the following monitoring tools or methods are appropriate for gaining these insights into Cortex LLM function costs and token consumption?

A. Option E

B. Option D

C. Option B

D. Option A

E. Option C

Correct Answer: A,B,C,D

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Question 11

A data engineering team needs to configure their Snowflake environment to process documents using AI_PARSE_DOCUMENT and generate text embeddings using EMBED_TEXT_1024 with the voyage-multilingual-2 model. Their Snowflake account is in a region where these specific capabilities or models are only available via cross-region inference. The team needs to ensure these functions work correctly without constant region-specific model selection. Which of the following is the correct configuration action and an important consideration?

A. Option E

B. Option D

C. Option B

D. Option A

E. Option C

Correct Answer: A,C

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Snowflake SnowPro® Specialty: Gen AI Certification - GES-C01 Exam Practice Test

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