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Snowflake GES-C01 Exam Syllabus Topics:

Snowflake SnowPro® Specialty: Gen AI Certification Sample Questions:

1. 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) 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

B) Cortex Search automatically handles text chunking and embedding generation for the source data, eliminating the need for manual ETL processes for these steps.
C) 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.
D) The
E) 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.

2. A financial services company uses Snowflake Cortex's AI_COMPLETE for sentiment analysis on customer call transcripts, which contain personally identifiable information (PII). They also fine-tune a llama3.1-70b model with proprietary financial data. Which of the following statements accurately describe Snowflake's Gen AI principles regarding data privacy, model usage, and governance in this scenario?

A) Snowflake's metadata fields, such as table and column names, should not contain personal, sensitive, or export-controlled data when using Snowflake AI services, to maintain data governance.
B) The fine-tuned llama3.1-70b model, including the proprietary training data used, is exclusively owned by the financial institution and is not shared with other Snowflake customers.
C) Customer Data (inputs and outputs) for AI_COMPLETE, including PII, are guaranteed not to be available to other customers or used to train models made available to others.
D) Enabling Cortex Guard for AI_COMPLETE automatically anonymizes all PII within the prompt before it reaches the LLM, regardless of the model chosen, to ensure privacy.
E) When using Cortex Analyst with Snowflake-hosted LLMs, metadata and prompts are transmitted outside Snowflake's governance boundary for processing, incurring additional cross-cloud data transfer costs.

3. A data engineer is integrating a custom application with Snowflake Cortex to leverage the 'COMPLETE' function via its REST API. They are preparing a 'curl' request to send a prompt to the 'mistral-large? model. Which of the following 'curl' command configurations correctly specifies the ''mandatory'' authentication header and a valid token type for accessing the Cortex REST API?

A)

B)

C)

D)

E)

4. A developer is building a conversational application using Snowflake Cortex Analyst and is interacting with it via the REST API. The application needs to support multi-turn conversations where users can ask follow-up questions. Which of the following statements accurately describe how to maintain conversational state and interact with the Cortex Analyst REST API for a multi-turn experience?

A) For performance optimization, only the most recent user prompt and the immediate preceding analyst response should be passed in the 'messages' array for follow-up questions.
B) To maintain state, the application must construct a 'messages' array for each new prompt, including all prior 'user' prompts and 'analyst' responses in chronological order, and send it with every API call.
C) The Cortex Analyst REST API automatically retains the full conversation history for each user session, eliminating the need to explicitly pass previous messages.
D) A special 'RESET_CONVERSATION' API endpoint should be called periodically to clear the LLM's internal context and manage token consumption for long conversations.
E) The argument, when using the 'COMPLETE function (or its API equivalent), must be a string for single-turn conversations but an array of objects for multi-turn conversations, with each object containing 'role' and 'content'.

5. 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 storage units within an image registry service, and they are used to store OCI-compliant 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) The maximum compressed layer size for an image registry is consistent across all cloud providers and regions, typically 160 GiB.
D) Dropping individual images from a repository is supported, allowing for granular management of stored container images.
E) Image repositories are primarily used for storing pre-trained Snowflake ML models and do not support custom third-party container images.

Solutions: