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Snowflake GES-C01 Exam Syllabus Topics:

Snowflake SnowPro® Specialty: Gen AI Certification Sample Questions:

1. A Snowflake account is located in the AWS US East 1 (N. Virginia) region. The 'ACCOUNTADMIN' has set the 'CORTEX MODELS ALLOWLIST' to "mistral-7b" and 'CORTEX ENABLED CROSS REGION' to 'ANY REGION'. A data scientist, whose role has only the 'SNOWFLAKE.CORTEX USER database role, performs several 'AI COMPLETE calls. Which of the following statements correctly describe the behavior of these calls under the given configuration?

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

2. A Streamlit application developer wants to use AI_COMPLETE (the latest version of COMPLETE (SNOWFLAKE.CORTEX)) to process customer feedback. The goal is to extract structured information, such as the customer's sentiment, product mentioned, and any specific issues, into a predictable JSON format for immediate database ingestion. Which configuration of the AI_COMPLETE function call is essential for achieving this structured output requirement?

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

3. A data engineer is tasked with establishing AI Observability for a generative AI application that integrates with external systems and will undergo continuous improvement. The goal is to compare different iterations of the application efficiently. Which combination of configuration best practices, features, and governance aspects are most relevant for a robust setup of AI Observability within Snowflake for this scenario?

A) Ensure the Python environment includes 'trulens-core', 'trulens-connectors-snowflake', and 'trulens-providers-cortex' (version 2.1.2 or later) and set the environment variable TRULENS_OTEL_TRACING to 1.
B) Run the AI Observability project directly within a Snowflake Notebook to leverage its integrated environment for easier debugging and iteration.
C) If the AI Observability service is not natively available in the primary region, enable to ' ANY_REGION' or a specific supported region to allow tracing and evaluation to proceed.
D) To compare different LLMs or prompt configurations, rely on the AI Observability's 'Comparisons' feature, which allows side-by-side analysis of evaluation metrics across multiple evaluations.
E) For access control, the role used to create and execute runs must be granted the 'SNOWFLAKE.CORTEX_USER database role and the 'AI_OBSERVABILITY_EVENTS_LOOKUPS application role.

4. A Gen AI specialist is preparing to upload a large volume of diverse documents to an internal stage for Document AI processing. The objective is to extract detailed information, including lists of items and potentially classifying document types, and then automate this process. Which of the following statements represent 'best practices or important considerations/limitations' when preparing documents and setting up the Document AI workflow in Snowflake? (Select ALL that apply.)

A) To improve model training, documents uploaded should represent a real use case, and the dataset should consist of diverse documents in terms of both layout and data.
B) When defining data values for extraction, especially for nonstandard formats or combinations of values, fine-tuning the model with annotations is generally more effective than relying solely on complex prompt engineering.
C) If the Document AI model does not find an answer for a specific field, the '!PREDICT method will omit the 'value' key but will still return a 'score' key to indicate confidence that the answer is not present.
D) For continuous processing of new documents, it is best practice to create a stream on the internal stage and a task to automate the '!PREDICT method execution.
E) Documents with a page count exceeding 125 pages or a file size greater than 50 MB will be processed, but with a potential reduction in extraction accuracy.

5. A data engineering team is building an automated pipeline in Snowflake to process incoming sensor dat a. Each sensor reading includes a 1024-dimensional feature vector, and the team needs to flag readings that are significantly different from a baseline reference vector using VECTOR_L1_DISTANCE
. The pipeline uses Snowflake tasks to orchestrate data loading and transformation. Which statement regarding the integration and operational aspects of this pipeline is true?

A) Snowflake Cortex AI SQL functions, including
B) The
C) To ensure efficient processing of new sensor data, the
D) For optimal performance when calculating
E) The

Solutions: