Snowflake GES-C01 exam dumps : SnowPro® Specialty: Gen AI Certification Exam

  • Exam Code: GES-C01
  • Exam Name: SnowPro® Specialty: Gen AI Certification Exam
  • Updated: Sep 30, 2026     Q & A: 351 Questions and Answers

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Snowflake GES-C01 Exam Syllabus Topics:

SectionObjectives
Snowflake AI & Cortex- Snowflake Cortex capabilities
- AI functions and services in Snowflake
Generative AI Fundamentals- Model capabilities and limitations
- Core concepts of generative AI and LLMs
Model Evaluation & Responsible AI- Bias, fairness, and explainability considerations
- Evaluation metrics for LLM outputs
Use Cases & Solution Design- End-to-end GenAI solution architecture
- Enterprise AI application patterns in Snowflake
Embeddings, Vector Search & RAG- Vector search in Snowflake ecosystem
- Retrieval-Augmented Generation (RAG) workflows
- Embeddings fundamentals
Prompt Engineering- Optimization of prompts for LLM outputs
- Prompt design techniques
Data Governance & Security- Responsible use of AI in enterprise environments
- Data privacy and access controls

Snowflake SnowPro® Specialty: Gen AI Certification Sample Questions:

Question #1

A development team plans to utilize Snowpark Container Services (SPCS) for deploying a variety of AI/ML workloads, including custom LLMs and GPU-accelerated model training jobs. They are in the process of creating a compute pool and need to select the appropriate instance families and configurations. Which of the following statements about 'CREATE COMPUTE POOL' in SPCS are accurate?

  • A. For cost optimization, 'AUTO SUSPEND SECS = 0' should be used to prevent automatic suspension of the compute pool, as suspension and resumption incur minimum billing durations.
  • B. Setting 'AUTO RESUME = TRUE ensures that the compute pool automatically starts when a service or job is submitted to it, rather than requiring manual resumption.
  • C. To support GPU-accelerated LLM inference and training, the 'INSTANCE_FAMILY' must be selected from a type starting with 'GPU' (e.g.,
  • D. Snowpark-optimized warehouses are the recommended compute pool type for all large-scale ML training workloads within SPCS due to their enhanced memory limits and CPU architectures.
  • E. The 'MIN NODES' and 'MAX NODES parameters define the scaling range for the compute pool, and Snowflake automatically scales the pool within this range based on workload demand.
Reveal Solution  Discussion  0

Correct Answer: B,C  🗳️

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Question #2

A company is implementing a Document AI solution to extract sensitive financial data from invoices. They plan to fine-tune the Document AI model (Arctic-TILT) and then manage this custom model within the Snowflake Model Registry. Which of the following statements correctly outlines the access control, data handling, and model management principles for this scenario?

  • A. Option D
  • B. Option A
  • C. Option E
  • D. Option C
  • E. Option B
Reveal Solution  Discussion  0

Correct Answer: B  🗳️

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Question #3

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 D
  • B. Option A
  • C. Option E
  • D. Option C
  • E. Option B
Reveal Solution  Discussion  0

Correct Answer: D  🗳️

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Question #4

A data engineering team wants to deploy a proprietary PyCaret classification model, saved as pycaret_best_model.pkl, for inference within Snowpark Container Services (SPCS). They need to register this custom model in the Snowflake Model Registry. Which of the following is a correct and essential step in this process?

  • A. Option D
  • B. Option A
  • C. Option E
  • D. Option C
  • E. Option B
Reveal Solution  Discussion  0

Correct Answer: E  🗳️

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Question #5

A data application developer is tasked with creating a multi-turn conversational AI application using Streamlit in Snowflake (SiS), which will leverage Snowflake Cortex LLM functions. Considering the core requirements for building such an interactive chat interface and the underlying Snowflake environment, which of the following actions is a fundamental step in setting up the application for stateful conversations?

  • A. Option D
  • B. Option A
  • C. Option E
  • D. Option C
  • E. Option B
Reveal Solution  Discussion  0

Correct Answer: E  🗳️

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