Passing exam with GES-C01 latest training materials
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Updated: Sep 10, 2026
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Snowflake GES-C01 Exam Overview:
| Certification Vendor: | Snowflake |
|---|---|
| Exam Name: | SnowPro® Specialty: Gen AI Certification Exam |
| Exam Number: | GES-C01 |
| Related Certifications: | SnowPro Core SnowPro Associate: Platform |
| Exam Price: | $225 USD |
| Exam Format: | Multiple-choice, Interactive scenario-based, Multiple-select |
| Certificate Validity Period: | 2 years |
| Exam Duration: | 85 minutes |
| Passing Score: | 750 (scaled 0–1000) |
| Available Languages: | English |
| Real Exam Qty: | 55 |
| Recommended Training: | Snowflake Gen AI Training Official Study Guide |
| Exam Registration: | Pearson VUE Registration |
| Sample Questions: | Snowflake GES-C01 Sample Questions |
| Exam Way: | Online proctored (OnVUE) or onsite at Pearson VUE test centers |
| Pre Condition: | Active SnowPro Core or SnowPro Associate: Platform certification; 1+ year Gen AI experience with Snowflake; proficiency in SQL, Python and data engineering concepts |
| Official Syllabus URL: | https://learn.snowflake.com/en/certifications/snowpro-GenAI/ |
Snowflake GES-C01 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Snowflake Gen AI Governance | 22% | - Cost management and token-based pricing - Guardrails, safety controls, and bias mitigation - Monitoring, logging, and observability - Audit and compliance for AI workloads - AI governance framework and policies |
| Snowflake for Gen AI Overview | 26% | - Role-based access control (RBAC) for AI resources - Snowflake Gen AI principles and best practices - Snowflake Copilot and AI assistant capabilities - Cortex AI components: Cortex Search, Cortex Analyst, Cortex LLMs |
| Snowflake Document AI | 12% | - Document preparation and processing - Performance optimization and troubleshooting - Document AI setup and configuration - Data extraction and structured output |
| Snowflake Gen AI & LLM Functions | 40% | - Cortex LLM functions: COMPLETE, CLASSIFY_TEXT, EXTRACT_ANSWER, SENTIMENT, SUMMARIZE, TRANSLATE - API integration and authentication - RAG implementation in Snowflake - Embedding functions: EMBED_TEXT_*, vector storage and similarity search - Model deployment with Snowpark Container Services and Model Registry |
Snowflake SnowPro® Specialty: Gen AI Certification Sample Questions:
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 E
- B. Option B
- C. Option C
- D. Option A
- E. Option D
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A financial services company is developing an automated data pipeline in Snowflake to process Federal Reserve Meeting Minutes, which are initially loaded as PDF documents. The pipeline needs to extract specific entities like the FED's stance on interest rates ('hawkish', 'dovish', or 'neutral') and the reasoning behind it, storing these as structured JSON objects within a Snowflake table. The goal is to ensure the output is always a valid JSON object with predefined keys. Which AI_COMPLETE configuration, used within an in-line SQL statement in a task, is most effective for achieving this structured extraction directly in the pipeline?
- A. Option E
- B. Option B
- C. Option C
- D. Option A
- E. Option D
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An analytics team needs to use various Snowflake Cortex LLM functions and wants to understand the cost implications and governance mechanisms for controlling model access and usage. The "ACCOUNTADMIN' has restricted general LLM access using the 'CORTEX_MODELS_ALLOWLIST' parameter. The team is particularly interested in how model complexity and specific function calls impact billing and how access can be managed effectively for different user groups.
- A. Option E
- B. Option B
- C. Option C
- D. Option A
- E. Option D
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An enterprise is deploying a new RAG application using Snowflake Cortex Search on a large dataset of customer support tickets. The operations team is concerned about managing compute costs and ensuring efficient index refreshes for the Cortex Search Service, which needs to be updated hourly. Which of the following considerations and configurations are relevant for optimizing cost and performance of the Cortex Search Service in this scenario?
- A. The
- B. For embedding text, selecting a model like
- C. CHANGE_TRACKING
- D. The primary cost driver for Cortex Search is the number of search queries executed against the service, with the volume of indexed data (GB/month) having a minimal impact on overall billing.
- E. For optimal performance and cost efficiency, Snowflake recommends using a dedicated warehouse of size no larger than MEDIUM for each Cortex Search Service.
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A security audit is being conducted for a financial institution using Snowflake Cortex. Which of the following statements accurately describe Snowflake's data safety and security guarantees concerning whether customer data, metadata, or prompts leave Snowflake's governance boundary to a third-party when using Cortex features, under the default Snowflake configurations for Cortex functions unless otherwise specified?
- A. For Cortex Analyst, if the legacy ENABLE_CORTEX_ANALYST_MODEL_AZURE_OPENAI account parameter is set to TRUE, customer metadata and prompts are transmitted to Azure OpenAI, but the underlying customer data is not.
- B. Models brought into Snowflake via Snowpark Container Services (BYOM) are treated as Snowflake's proprietary models, meaning Snowflake assumes responsibility for their data handling policies.
- C. Customer Data and inputs to Snowflake AI Features are never used by Snowflake to train or fine-tune models made available to other customers.
- D. When CORTEX_ENABLED_CROSS_REGION is active for Cortex LLM functions, user inputs and outputs are always cached in the intermediate region to reduce latency, thereby leaving the primary region's immediate governance.
- E. When using SNOWFLAKE .CORTEX. COMPLETE with Snowflake-hosted LLMs like all prompts and generated responses remain within Snowflake's mistral-large2, governance boundary by default.
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