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Snowflake GES-C01 Exam Syllabus Topics:

Snowflake SnowPro® Specialty: Gen AI Certification Sample Questions:

1. A financial institution wants to automate the extraction of key entities (e.g., invoice number, total amount, list of invoice items) from incoming PDF financial statements into a structured JSON format within their Snowflake data pipeline. The extracted data must conform to a specified JSON schema for seamless downstream integration. Which Snowflake Cortex capabilities, when combined, can best achieve this data augmentation and ensure schema adherence in a continuous processing pipeline?

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

2. A Data Engineer is responsible for deploying machine learning models using Snowpark Container Services. They need to ensure that a specific role, model_deployer_role, has the appropriate permissions to create a Snowpark Container Service that uses an image from an existing image repository named my_inferenc_ images. Which of the following SQL commands grant the necessary privileges 'on the image repository' for this purpose?

A)

B)

C)

D)

E)

3. A Snowflake account administrator in an Azure East US 2 region needs to enable users to access a new, highly capable LLM, 'claude-3-5-sonnet' , which is currently only natively available in AWS regions via Snowflake Cortex. The administrator also wants to ensure that only specific, approved LLMs can be used across the organization. Which configuration steps are necessary for the administrator to achieve these requirements?

A) Since 'claude-3-5-sonnet' is an OpenAl model, the administrator must enable the 'ENABLE_CORTEX ANALYST MODEL AZURE OPENAI' account parameter, and then the model will automatically be available for cross-region inference without further action.
B) Grant the 'SNOWFLAKE.CORTEX_USER database role to the relevant user roles. Set the account parameter to 'ANY REGION' or a list including an AWS region where 'claude-3-5-sonnet' is natively available. Additionally, configure the 'CORTEX MODELS ALLOWLIST to explicitly permit 'claude-3-5-sonnet' and other desired models.
C) Create a 'COMPUTE POOL' with a 'GPU NV_S instance family in Azure East US 2, and then deploy a custom PyCaret model of 'claude-3-5-sonnet' to this pool through the Snowflake Model Registry.
D) The 'CORTEX ENABLED CROSS REGION' parameter allows access to models in other regions, but access to specific LLMs is controlled solely by individual user privileges granted directly on the model objects, not by an account-level allowlist.
E) Set the account parameter to include 'claude-3-5-sonnet' , and then set the account parameter to 'TRUE to allow cross-region inference for all Cortex features.

4. An ML engineer is deploying a custom PyTorch-based image classification model, obtained from Hugging Face, to Snowpark Container Services (SPCS). The deployment requires GPU acceleration on a compute pool named 'my_gpu_pool' and specific Python packages ('torch' , 'transformers' , 'opencv-python'). The scenario dictates that 'opencv-python' is only available via PyPl, while 'torch' and 'transformers' can be sourced from either conda-forge or PyPl. The engineer uses the Snowflake Model Registry to log the model. Which of the following and configurations correctly specify the necessary Python dependencies and GPU utilization for this inference service, adhering to Snowflake's recommendations?

A)

B)

C)

D)

E)

5. A machine learning engineer is building a product recommendation system in Snowflake that uses item embeddings and customer query embeddings for similarity matching. They plan to use the VECTOR_L1_DISTANCE function to find the closest products to a user's query. Which statement accurately describes the cost and data type considerations for this approach?

A) Both

B) The
C) The maximum dimension for a
D) Storing the item and query embeddings in
E) Executing the

Solutions: