Free Snowflake GES-C01 Exam Questions

Core Snowflake Gen AI Technologies:

• Snowflake Cortex - LLMs, Cortex Search, Cortex Analyst, Cortex Fine-tuning, Cortex Agents (Public Preview)
• Snowflake Copilot - AI-powered assistance for SQL development
• Security, Privacy, Access, and Control - RBAC, Guardrails, Required privileges, CORTEX_MODELS_ALLOWLIST parameter
• Cortex LLM Functions - Control model access, Cortex LLM Playground (Public Preview), SQL, REST API
• Bring Your Own Models - Snowflake Model Registry (custom models), Snowpark Container Services (e.g., Hugging Face)
• Vector Functions - VECTOR_INNER_PRODUCT, VECTOR_L1_DISTANCE, VECTOR_L2_DISTANCE, VECTOR_COSINE_SIMILARITY
• Cross-region Inference - CORTEX_ENABLED_CROSS_REGION parameter, latency and availability considerations
• Document AI - Model setup, training, troubleshooting, and extraction from documents

Exam Sections (4 Main Domains with Weightings):

1. Domain 1.0: Snowflake for Gen AI Overview (26%) - Define Snowflake's Gen AI principles, features, and best practices; Outline Gen AI capabilities in Snowflake including Cortex LLM functions, Cortex Search, Cortex Analyst, Cortex Fine-tuning, Cortex Agents, and Snowflake Copilot
2. Domain 2.0: Snowflake Gen AI & LLM Functions (40%) - Apply Gen AI and LLM functions in Snowflake (COMPLETE, task-specific functions like CLASSIFY_TEXT, EXTRACT_ANSWER, PARSE_DOCUMENT, SENTIMENT, SUMMARIZE, TRANSLATE, EMBED_TEXT); Perform data analysis using fully-managed LLMs, RAG, and text-to-SQL services; Build chat interfaces to interact with data; Use Cortex functions in data pipelines; Run third-party models in Snowflake using Snowpark Container Services and Model Registry
3. Domain 3.0: Snowflake Gen AI Governance (22%) - Set up model access controls (CORTEX_MODELS_ALLOWLIST parameter); Set guardrails to filter harmful or unsafe LLM responses (Cortex Guard); Monitor and optimize Snowflake Cortex costs (Cortex Search, Cortex Analyst, Cortex LLM functions, usage tracking); Use Snowflake AI observability tools (evaluation metrics, comparisons, tracing, logging, event tables)
4. Domain 4.0: Snowflake Document AI (12%) - Set up Document AI (virtual warehouse, database, schema considerations, roles and privileges); Prepare documents for Document AI (upload, train model, requirements, question optimization); Extract values from documents using Document AI (conditions, PREDICT query, automation); Troubleshoot Document AI given a use case (extracting query errors, GET_PRESIGNED_URL function, requirements and privileges, cost considerations)

Key Skills Tested:

• Define and implement Snowflake Gen AI principles, capabilities, and best practices related to infrastructure, data governance, and cost governance
• Leverage Snowflake Cortex AI features, Large Language Models (LLMs), and offerings to support customer use cases (Cortex Analyst, Cortex Search, Cortex Fine-tuning, Snowflake Copilot)
• Build open-source models with Snowpark Container Services and Snowflake Model Registry (e.g., Hugging Face)
• Use Document AI to train and troubleshoot models specific to authentic use cases
• Build Retrieval Augmented Generation (RAG) applications leveraging LLMs
• Implement chat interfaces and multi-turn conversations with data in Snowflake
• Apply Cortex functions in data pipelines for data enrichment, augmentation, and transformations