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

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Snowflake GES-C01 Exam Syllabus Topics:

Snowflake SnowPro® Specialty: Gen AI Certification Sample Questions:

1. A developer is integrating a Cortex Fine-tuning pipeline into an automated data workflow and needs to ensure structured outputs and monitor the process effectively. They are also aware of certain architectural limitations within Snowflake. Which of the following statements regarding advanced usage or limitations of Snowflake Cortex Fine-tuning and related LLM functions are accurate? (Select all that apply)

A) Fine-tuning jobs, being long-running processes, are inherently tied to the worksheet session where they are initiated, and terminating the session will interrupt the training.
B) The regional availability of the
C) Snowflake Cortex Fine-tuning functions inherently support dynamic tables as sources for training data, allowing for automated and continuous re-training as the underlying data evolves.
D) After initiating a fine-tuning job using the
E) To achieve the most consistent and deterministic results from a fine-tuned LLM during inference, the temperature option in the

2. A data analyst is using Snowflake Copilot in Snowsight to generate SQL queries for a new dataset containing customer PII. Which of the following statements accurately describes how Snowflake Copilot operates with respect to data access, governance, and model interaction?

A) Snowflake Copilot requires explicit column-level grants for direct data access, similar to how a human analyst would query specific data points.
B) To protect sensitive information, Snowflake Copilot transmits sampled PII data to an external LLM for schema understanding before generating SQL.
C) Snowflake Copilot is powered by a fine-tuned model that runs securely inside Snowflake Cortex, leveraging only database/schema/table/column names and data types, ensuring data remains within Snowflake's governance boundary and respects RBAC.
D) Snowflake Copilot directly accesses and processes the raw data within customer tables to understand its content and generate SQL.
E) While Snowflake Copilot generates SQL based on metadata, the generated SQL queries are executed in an isolated environment that does not respect existing Snowflake RBAC policies.

3. A financial institution wants to leverage Snowflake Cortex Agents to build an AI application for complex financial analysis, requiring interaction with both their structured transaction databases and unstructured legal documents, while also ensuring intelligent decision- making throughout the process. Which of the following accurately describe the foundational capabilities of Snowflake Cortex Agents?

A) Allows integration of custom logic and external services through user-defined functions (UDFs) and stored procedures as custom tools.
B) Cortex Agents primarily focus on providing a low-latency, hybrid (vector and keyword) search engine over text data.
C) Agents are designed to orchestrate tasks by planning execution steps, and utilizing tools such as Cortex Analyst for structured data and Cortex Search for unstructured data.
D) Cortex Agents enable direct fine-tuning of base LLMs using private customer data, with the resulting models managed within the Snowflake Model Registry.
E) They incorporate a 'Reflection' component, allowing the agent to evaluate results after each tool use and determine the next logical steps, including iterating or clarifying.

4. 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)

5. An analytics team is preparing documents for a new Document AI model build to extract information from internal policy reviews. They have a variety of documents that they intend to upload to an internal stage for processing. The document list includes: (1 ) a 70 MB PDF with 100 pages, (2) a 45 MB DOCX with 150 pages, (3) a 30 MB PNG image, (4) a 60 MB TIFF image, and (5) a 20 MB HTML file. All documents are in English. Which of these documents would 'fail' to meet the direct input requirements for Document AI processing?

A) The 45 MB DOCX with 150 pages.
B) The 60 MB TIFF image.
C) The 20 MB HTML file.
D) The 70 MB PDF with 100 pages.
E) The 30 MB PNG image.

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