Snowflake GES-C01 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Topic 1: Model Evaluation & Responsible AI | - Evaluation metrics for LLM outputs - Bias, fairness, and explainability considerations |
| Topic 2: Use Cases & Solution Design | - Enterprise AI application patterns in Snowflake - End-to-end GenAI solution architecture |
| Topic 3: Prompt Engineering | - Optimization of prompts for LLM outputs - Prompt design techniques |
| Topic 4: Generative AI Fundamentals | - Core concepts of generative AI and LLMs - Model capabilities and limitations |
| Topic 5: Data Governance & Security | - Responsible use of AI in enterprise environments - Data privacy and access controls |
| Topic 6: Embeddings, Vector Search & RAG | - Vector search in Snowflake ecosystem - Embeddings fundamentals - Retrieval-Augmented Generation (RAG) workflows |
| Topic 7: Snowflake AI & Cortex | - AI functions and services in Snowflake - Snowflake Cortex capabilities |
Snowflake SnowPro® Specialty: Gen AI Certification Sample Questions:
1. A data engineer is integrating a custom application with Snowflake Cortex to leverage the 'COMPLETE' function via its REST API. They are preparing a 'curl' request to send a prompt to the 'mistral-large? model. Which of the following 'curl' command configurations correctly specifies the ''mandatory'' authentication header and a valid token type for accessing the Cortex REST API?
A)
B)
C)
D)
E) 
2. 
A)
B)
C) Data for all these operations remains within Snowflake's governance boundary.
D)
E) 
3. An AI developer is building a Snowflake data pipeline to prepare unstructured data for a RAG application. The pipeline involves extracting text, splitting it into chunks, generating embeddings, and then indexing for Cortex Search. Considering the role of helper functions like SNOWFLAKE.CORTEX.SPLIT_TEXT_RECURSIVE_CHARACTER
, which of the following statements accurately describes its typical operational placement and interaction within this Gen AI pipeline?
A) Its output, consisting of smaller text chunks, serves as the direct input for text embedding functions that then convert these chunks into vector representations for semantic indexing.
B) It replaces the need for
C) It is typically applied after an embedding function (e.g.,
D) The function's recursive nature enables it to automatically detect and correct factual inconsistencies or 'hallucinations' present in the original large text documents before they are embedded.
E) It is a post-processing step for LLM-generated responses, used to break down long answers into digestible paragraphs for user display in chat interfaces.
4. A Snowflake administrator needs to implement a granular access control strategy for LLMs. The general policy is to restrict access to a select few models via an account-level allowlist. However, a specific data science team (using role 'DATA SCIENCE TEAM ROLE) requires access to the 'claude-3-5-sonnet' model, which should not be available to other users or globally via the allowlist. Given this scenario, which set of commands would correctly establish this access control while adhering to the specified requirements?
A)
B)
C)
D)
E) 
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 A
B) Option E
C) Option D
D) Option C
E) Option B
Solutions:
| Question # 1 Answer: A | Question # 2 Answer: C | Question # 3 Answer: A | Question # 4 Answer: A | Question # 5 Answer: E |














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