SnowPro® Specialty: Gen AI Certification Exam: GES-C01 Exam
"SnowPro® Specialty: Gen AI Certification Exam", also known as GES-C01 exam, is a Snowflake Certification. With the complete collection of questions and answers, PrepPDF has assembled to take you through 351 Q&As to your GES-C01 Exam preparation. In the GES-C01 exam resources, you will cover every field and category in Snowflake Certification Certification helping to ready you for your successful Snowflake Certification.
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- Exam Code: GES-C01
- Exam Name: SnowPro® Specialty: Gen AI Certification Exam
- Certification Provider: Snowflake
- Corresponding Certification: Snowflake Certification
- Updated: Aug 11, 2026
- No. of Questions: 351 Questions & Answers with Testing Engine
- Download Limit: Unlimited
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Snowflake GES-C01 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Topic 1: Embeddings, Vector Search & RAG | - Retrieval-Augmented Generation (RAG) workflows - Embeddings fundamentals - Vector search in Snowflake ecosystem |
| Topic 2: Use Cases & Solution Design | - Enterprise AI application patterns in Snowflake - End-to-end GenAI solution architecture |
| Topic 3: Data Governance & Security | - Responsible use of AI in enterprise environments - Data privacy and access controls |
| Topic 4: Model Evaluation & Responsible AI | - Bias, fairness, and explainability considerations - Evaluation metrics for LLM outputs |
| Topic 5: Snowflake AI & Cortex | - Snowflake Cortex capabilities - AI functions and services in Snowflake |
| Topic 6: Generative AI Fundamentals | - Model capabilities and limitations - Core concepts of generative AI and LLMs |
| Topic 7: Prompt Engineering | - Optimization of prompts for LLM outputs - Prompt design techniques |
Snowflake SnowPro® Specialty: Gen AI Certification Sample Questions:
1. A Snowflake Gen AI Specialist is defining a semantic model for Cortex Analyst to improve text-to-SQL accuracy. They are adding entries to the verified _ queries section of their YAML file. Consider the following semantic model snippet and a proposed verified_query entry. Which of the following statements correctly identifies an issue or a best practice not followed in the sql field of the proposed verified_query entry, based on Cortex Analyst VQR guidelines? Semantic Model Snippet:
Proposed verified _ query entry:

A) Option A
B) Option C
C) Option D
D) Option B
E) Option E
2. 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) 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.
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) 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.
E) 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.
3. A Snowflake user attempts to access the Cortex Playground to experiment with LLM functions but receives an error indicating insufficient privileges. They have an active Snowflake session. Which of the following steps must be taken to ensure they can successfully use the Cortex Playground?
A) Option A
B) Option C
C) Option D
D) Option B
E) Option E
4. 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 C
C) Option D
D) Option B
E) Option E
5. A Snowflake administrator is tasked with monitoring the efficiency and cost-effectiveness of their Cortex Analyst deployments. They need to identify if certain semantic models are generating a high volume of failed or expensive queries. Which of the following approaches or statements are crucial for effectively monitoring and identifying issues with Cortex Analyst usage and associated costs?
A) Option A
B) Option C
C) Option D
D) Option B
E) Option E
Solutions:
| Question # 1 Answer: B,D | Question # 2 Answer: A,C,D,E | Question # 3 Answer: A,C | Question # 4 Answer: B | Question # 5 Answer: A,B,E |
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