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| Section | Weight | Objectives |
|---|---|---|
| Generative AI Fundamentals and Concepts | 20-25% | - Prompt engineering principles - Vector embeddings and similarity search - Retrieval-Augmented Generation (RAG) concepts - Fine-tuning vs. retrieval approaches - LLM fundamentals and architectures |
| Data Preparation for Gen AI | 15-20% | - Document processing and chunking strategies - Vector stores and embeddings in Snowflake - Data governance for AI workloads - Unstructured data handling |
| Architecture and Best Practices | 10-15% | - LLM pipeline architecture design - Security and privacy considerations - Monitoring and evaluation frameworks - Cost management strategies - Performance optimization techniques |
| Cortex Analyst and Semantic Layer | 20-25% | - Business logic implementation in semantic models - Text-to-SQL translation and optimization - Performance tuning for analytical queries - Semantic model design and configuration |
| Snowflake Cortex AI Capabilities | 25-30% | - Snowflake Copilot integration - COMPLETE function usage and parameters - Cortex AI functions and features - Model selection and cost optimization - Secure data handling in AI workflows |
An organization enforces strict LLM access control. The has configured 'CORTEX MODELS_ALLOWLIST ='mistral-large2" and executed 'CALL SNOWFLAKE.MODELS.CORTEX BASE MODELS REFRESH()'. A developer, whose role DEV ROLE has been granted 'SNOWFLAKE.CORTEX USER' and 'SNOWFLAKE."CORTEX-MODEL-ROLE-CLAUDE-3-5- SONNET"' , attempts to make a REST API call to 'api/v2/cortex/inference:complete' using 'claude-3-5-sonnet' as the model name in the request body. Which of the following statements are true regarding this scenario?
Correct Answer: B,D 🗳️
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A data engineer is building a Snowflake data pipeline to ingest customer reviews from a raw staging table into a processed table. For each review, they need to determine the overall sentiment (positive, neutral, negative) and store this as a distinct column. The pipeline is implemented using SQL with streams and tasks to process new dat a. Which Snowflake Cortex LLM function, when integrated into the SQL task, is best suited for this sentiment classification and ensures a structured, single-label output for each review?
Correct Answer: D 🗳️
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A large e-commerce company plans to implement real-time sentiment analysis on millions of incoming customer reviews using SNOWFLAKE. CORTEX. SENTIMENT. They are concerned about managing costs and ensuring efficient processing. Which of the following statements about cost considerations and performance optimizations for SNOWFLAKE. CORTEX. SENTIMENT are true?
(Select all that apply)
Correct Answer: A,C,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.
Correct Answer: B,C,E 🗳️
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A data science team is deploying a custom real-time inference service for a fine-tuned LLM using Snowpark Container Services (SPCS). They have a Docker image in their Snowflake image repository. They need to define the service using a YAML specification file. Which of the following are ''essential'' components or configurations that must be included in the 'spec.yaml'' file for a long- running service that uses this image, custom environment variables, and requires external access?





Correct Answer: A,C,E 🗳️
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