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Snowflake SnowPro® Specialty: Gen AI Certification Sample Questions:
1. A data scientist has developed a Hugging Face sentence transformer model for semantic search and needs to deploy it for GPU- powered inference using Snowpark Container Services (SPCS) in Snowflake. They've already trained the SentenceTransformer model locally. Which of the following statements correctly describe essential considerations for logging and deploying this model, ensuring it leverages GPU resources and appropriate dependencies?
A) Option B
B) Option E
C) Option D
D) Option C
E) Option A
2. An ML Engineer has developed a custom PyTorch model for image processing that requires GPU acceleration and specific PyPl packages ('torch' , 'torchvision'). They want to deploy it as a service on Snowpark Container Services (SPCS) using the Snowflake Model Registry. Which of the following statements are true regarding the deployment of this model to SPCS and its requirements? (Select all that apply.)
A) Option B
B) Option E
C) Option D
D) Option C
E) Option A
3. An operations manager is tasked with monitoring the cost and ensuring compliance for a Cortex Analyst deployment that uses the REST API. They are particularly concerned with accurately tracking credit consumption and understanding the implications of enabling external models. Which of the following statements correctly describe aspects of Cortex Analyst cost and governance?
A) Snowflake's view provides granular usage information for REST API requests to cortex Analyst, including tokens processed per model.
B) Credit consumption for Cortex Analyst is primarily based on the number of tokens processed by the underlying LLMs, with more complex natural language questions leading to higher token usage and costs.
C) Cortex Analyst credit usage is based on the number of messages processed, at a rate of 67 Credits per 1 ,000 messages, and only successful responses (HTTP 200) are counted.
D) Enabling Azure OpenAI models via the ' ENABLE_CORTEX_ANALYST_MODEL_AZURE_OPENAF parameter ensures that all customer data and prompts remain within Snowflake's governance boundary and fully respect RBAC policies for those models.
E) The view can be queried to track detailed information about cortex Analyst requests, including generated SQL and any errors.
4. 
A) Cross-region inference is automatically managed by Snowflake for allowed models, implying that a new, larger virtual warehouse is required to handle the cross- region data transfer overhead.
B)
C)
D)
E) 
5. A data engineering team is building an automated pipeline in Snowflake to process incoming sensor dat a. Each sensor reading includes a 1024-dimensional feature vector, and the team needs to flag readings that are significantly different from a baseline reference vector using VECTOR_L1_DISTANCE
. The pipeline uses Snowflake tasks to orchestrate data loading and transformation. Which statement regarding the integration and operational aspects of this pipeline is true?
A) Snowflake Cortex AI SQL functions, including
B) For optimal performance when calculating
C) The
D) To ensure efficient processing of new sensor data, the
E) The
Solutions:
| Question # 1 Answer: A,B,D | Question # 2 Answer: A,C,D | Question # 3 Answer: C | Question # 4 Answer: C | Question # 5 Answer: C |



