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Snowflake GES-C01 Exam Syllabus Topics:

Snowflake SnowPro® Specialty: Gen AI Certification Sample Questions:

1. 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 A
B) Option C
C) Option D
D) Option B
E) Option E

2.
Which 'combination of missing schema-level privileges' is explicitly cited in the documentation as a direct cause for this error, assuming a unique model build name?

A)

B)

C)

D)

E)

3. A Gen AI Specialist is tasked with enhancing a Cortex Analyst semantic model to improve the accuracy of literal string searches for product names within user queries. The product names are stored in a high-cardinality PRODUCT_NAME column in the underlying PRODUCT table. The current semantic model already defines a dimension for PRODUCT_NAME. Which of the following configurations and considerations are essential for integrating Cortex Search with Cortex Analyst to achieve this goal?

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

4. A financial analytics team is using AI_COMPLETE to extract specific financial metrics (e.g., revenue, profit margin) from quarterly reports and requires the output in a strict JSON format for automated ingestion into a data warehouse. They've encountered issues where the LLM sometimes generates malformed JSON or includes extraneous text. Which of the following approaches will help ensure deterministic, schema-compliant JSON outputs and mitigate these 'hallucinations' related to format?

A) Include a prompt instruction such as 'Respond in JSON' to improve adherence, especially for complex tasks, even though 'response_format' is provided.
B)

C)

D)

E) Set the 'temperature' option to 0 when calling 'AI_COMPLETE' to obtain the most consistent and deterministic JSON outputs.

5. An organization operating in the AWS US West 2 (Oregon) region needs to process sensitive customer support tickets using Snowflake Cortex LLM functions. Due to the diverse availability of specific LLMs, they are considering enabling CORTEX_ENABLED_CROSS_REGION. What is a key data safety and security consideration when enabling CORTEX_ENABLED_CROSS_REGION for Snowflake Cortex LLM functions, specifically regarding data storage and persistence?

A) Data transmitted across regions for inference is encrypted by default, but the encryption keys are managed by the third-party cloud provider in the remote region.
B) User inputs and service-generated prompts will be stored in a cache in the remote region to optimize subsequent requests.
C) It enables inference for features not supported in the local region by allowing data to be processed in a different Snowflake region, and user inputs, prompts, and outputs are not stored or cached.
D) It may lead to increased compute costs if the cross-region model is more expensive, but data movement guarantees remain unchanged.
E)

Solutions: