- Exam Code: GES-C01
- Exam Name: SnowPro® Specialty: Gen AI Certification Exam
- Certification Provider: Snowflake
- Corresponding Certification:Snowflake Certification
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Snowflake GES-C01 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Snowflake Cortex AI Capabilities | 25-30% | - Secure data handling in AI workflows - COMPLETE function usage and parameters - Model selection and cost optimization - Snowflake Copilot integration - Cortex AI functions and features |
| Cortex Analyst and Semantic Layer | 20-25% | - Performance tuning for analytical queries - Semantic model design and configuration - Business logic implementation in semantic models - Text-to-SQL translation and optimization |
| Architecture and Best Practices | 10-15% | - Security and privacy considerations - Monitoring and evaluation frameworks - Cost management strategies - Performance optimization techniques - LLM pipeline architecture design |
| Generative AI Fundamentals and Concepts | 20-25% | - Retrieval-Augmented Generation (RAG) concepts - Prompt engineering principles - LLM fundamentals and architectures - Fine-tuning vs. retrieval approaches - Vector embeddings and similarity search |
| Data Preparation for Gen AI | 15-20% | - Vector stores and embeddings in Snowflake - Data governance for AI workloads - Document processing and chunking strategies - Unstructured data handling |
Snowflake SnowPro® Specialty: Gen AI Certification Sample Questions:
An enterprise is deploying a Cortex Analyst application and needs to manage its cost, ensure data security, and understand its operational behavior within Snowflake. Which of the following statements are true regarding the deployment, cost, and security of Cortex Analyst and its semantic models?
- A. Semantic models for Cortex Analyst, whether stored as YAML files or native semantic views, should have their access controlled by RBAC. This implicitly controls access to the underlying tables referenced in the semantic model.
- B. The primary cost incurred for Cortex Analyst is based on the number of tokens processed by the underlying LLMs, with more complex natural language questions directly leading to higher token usage and charges.
- C. When using Snowflake-hosted LLMs (e.g., from Mistral or Meta) with Cortex Analyst, all customer data, including metadata and prompts, remains within Snowflake's governance boundary.
- D. Snowflake strongly recommends enabling the ENABLE_CORTEX_ANALYST_MODEL_AZURE_OPENAI account parameter to leverage Azure OpenAI models for Cortex Analyst, as it offers the highest performance and respects RBAC restrictions for these models.
- E. Administrators can monitor Cortex Analyst requests, including the user, question asked, generated SQL, and errors, by querying the SNOWFLAKLOCAL .CORTEX_ANALYST_REQUESTS function.
Explanation: Only visible for TrainingDump members. You can sign-up / login (it's free).
A Gen AI Specialist is tasked with enhancing a Cortex Analyst semantic model to improve the accuracy of literal string searches for product names within user queries. The product names are stored in a high-cardinality PRODUCT_NAME column in the underlying PRODUCT table. The current semantic model already defines a dimension for PRODUCT_NAME. Which of the following configurations and considerations are essential for integrating Cortex Search with Cortex Analyst to achieve this goal?
- A. Option E
- B. Option D
- C. Option B
- D. Option A
- E. Option C
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A global enterprise has Snowflake accounts in various regions, including a US East (Ohio) account where a critical application is deployed. They need to use AI_COMPLETE with the claude-3-5-sonnet model for real-time customer support, but this model is not natively available in US East (Ohio) for direct AI_COMPLETE usage. The Snowflake administrator considers enabling cross-region inference. Which statements accurately reflect the considerations and characteristics of cross-region inference in Snowflake Cortex?
- A. Option E
- B. Option D
- C. Option B
- D. Option A
- E. Option C
Explanation: Only visible for TrainingDump members. You can sign-up / login (it's free).
A data scientist needs to generate vector embeddings for product descriptions stored in a column 'PRODUCT_DESCRIPTION' in the 'PRODUCT_CATALOG' table. They want to use the 'e5-base-v2 model for this task. Which of the following SQL statements correctly applies the 'SNOWFLAKE.CORTEX.EMBED TEXT 768' function and accurately describes the expected data type of the resulting embedding?
- A. The query
- B. The query
- C. The query
- D. The query
- E. The query
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A data engineer is setting up a Document AI pipeline to extract information from scanned invoices stored in an internal stage named 'invoice_stage'. They have created the stage using 'CREATE STAGE and uploaded several PDF documents. However, when attempting to run the extraction query, they encounter an error message: 'File extension does not match actual mime type. Mime- Type: application/octet-stream'. Additionally, they anticipate a privilege issue might arise for pipeline automation. Which of the following conditions must be met to resolve the current error and ensure proper setup for Document AI extraction and subsequent pipeline creation?
- A. Option E
- B. Option D
- C. Option B
- D. Option A
- E. Option C
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