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[General] GES-C01 examkiller gültige Ausbildung Dumps & GES-C01 Prüfung Überprüfu

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【General】 GES-C01 examkiller gültige Ausbildung Dumps & GES-C01 Prüfung Überprüfu

Posted at 4 day before      View：44 | Replies：1        Print      Only Author   [Copy Link] 1#
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Snowflake SnowPro® Specialty: Gen AI Certification Exam GES-C01 Prüfungsfragen mit Lösungen (Q298-Q303):298. Frage
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. 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.
  • 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. 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.
  • E. 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.
Antwort: B,C
Begründung:
Option A is correct. GPU-accelerated workloads, such as LLM inference and model training, require instance families specifically designed with GPUs. The documentation lists instance family names starting with 'GPU' for this purpose, such as or 'GPU_GCP NV L4 Option B is incorrect. While 'MIN NODES and 'MAX NODES define the range, the size of compute clusters in Snowpark Container Services does ''not'' auto-scale dynamically based on workload demand. Users must manually alter the number of instances at runtime using commands like 'ALTER SERVICE MIN INSTANCES = s. Snowflake does handle load balancing across instances within the configured node counts. Option C is correct. The 'AUTO_RESUME = TRUE parameter, when specified during compute pool creation, enables the pool to automatically resume operation when a service or job is submitted, removing the need for explicit SALTER COMPUTE POOL RESUME commands. option D is incorrect. Setting = prevents the compute pool from automatically suspending, meaning it will continue to consume credits even when idle. This would generally lead to higher costs, not cost optimization, unless the pool is constantly active. The default is 3600 seconds (1 hour). SPCS Compute Nodes have a minimum charge of five minutes when started or resumed, making intelligent use of auto-suspend important for cost management. Option E is incorrect. Snowpark-optimized warehouses are a type of 'virtual warehouse' and are recommended for Snowpark workloads with large memory requirements or specific CPU architecture, typically for single-node ML training workloads 'within a warehouse'. SPCS compute pools, however, provide their own dedicated instance families (CPU, HighMemory, GPU) for containerized workloads, abstracting the underlying infrastructure and supporting distributed GPU clusters directly within SPCS, not Snowpark-optimized warehouses as a 'compute pool type' for SPCS.

299. Frage
A data engineer is designing an automated pipeline in Snowflake to process streaming customer support tickets using LLM functions. To ensure the pipeline is robust against unexpected LLM errors (e.g., due to malformed input or transient service issues), they decide to use SNOWFLAKE.CORTEX.TRY_COMPLETE instead of SNOWF LAKE .CORTEX.COMPLETE
. Which of the following is the most significant advantage of using
TRY_COMPLETE
in this scenario?
  • A. It processes tokens at a significantly reduced rate compared to
  • B. It returns
  • C. It automatically adjusts the LLM's
  • D. It offers enhanced security features, such as automatic input sanitization, which are not available in the standard
  • E. It provides a built-in retry mechanism for LLM calls that encounter temporary failures, automatically re-submitting the prompt up to three times.
Antwort: B
Begründung:
Option C is correct because

instead of raising an error when the operation cannot be performed. This feature is crucial for building robust data pipelines, as it allows the pipeline to gracefully handle individual LLM call failures and continue processing other records, preventing the entire task from halting. Option A is incorrect; the sources do not mention an automatic retry mechanism for


300. Frage
A data engineer is building an AI data pipeline to automatically extract specific sentiment categories from customer reviews using 'AI_COMPLETE. They want the output to be a structured JSON object containing 'food_quality', 'food_taste', 'wait_time', and 'food cost' with their respective sentiments (e.g., 'positive', 'negative', 'neutral'). The engineer aims for high accuracy and ensures that all these fields are present in the output. Which of the following statements correctly describe the approach to achieve this?
  • A. The 'temperature' option should be set to a high value (e.g., 0.9) in the 'CompleteOptionS to encourage the model to strictly adhere to the specified JSON schema and reduce non-deterministic responses.
  • B. To improve accuracy, the JSON schema should include detailed descriptions for each field (e.g., 'food_quality', 'food_taste') to guide the model more precisely in identifying and extracting the sentiments.
  • C. When using OpenAl (GPT) models for structured output, the 'additionalPropertieS field must be set to 'true' in every node of the schema to allow for flexibility in the generated JSON.
  • D. For optimal accuracy in structured output, it is always best to explicitly instruct the LLM within the prompt to 'Respond in JSON' and provide a detailed description of the schema, regardless of task complexity.
  • E. The 'response_format' argument in 'AI COMPLETE should specify a JSON schema, and to ensure all fields are present, the 'required' field must be explicitly set for all desired properties in the schema.
Antwort: B,E
Begründung:
Option A is correct. The argument is used to supply a JSON schema that completion responses must follow, and including the 'required' field in the schema ensures that specified fields are present in the output, with raising an error if a required field cannot be extracted. Option B is incorrect. While prompting the model to 'Respond in JSON' can improve accuracy for complex tasks, it is not always necessary for simple tasks, as 'AI_COMPLETE Structured OutputS already understands that its response should conform to the specified schema. Option C is incorrect. For OpenAl (GPT) models, the 'additionalPropertieS field must be set to 'false' in every node of the schema. Option D is correct. Providing detailed descriptions of the fields to be extracted helps the model more accurately identify them, thereby improving the quality of the structured output. Option E is incorrect. For the most consistent results, it is recommended to set the 'temperature' option to 0 when calling 'COMPLETE (or regardless of the task or model, to make the output more deterministic and focused.

301. Frage
A Snowflake developer, named ANALYST USER, is tasked with creating a Streamlit in Snowflake (SiS) application that will utilize both SNOWFLAKE. CORTEX. COMPLETE for generating responses and SNOWFLAKE. CORTEX.CLASSIFY_TEXT for categorizing user input. To ensure the role used by ANALYST USER has the necessary permissions for executing these Cortex LLM functions and operating within a specified database and schema, which of the following database roles or privileges must be granted? (Select all that apply.)
  • A.
  • B.
  • C. The USAGE privilege on the database and schema where the Streamlit application runs and potentially stores related data.
  • D.
  • E.
Antwort: C,D
Begründung:
To execute Snowflake Cortex AI functions such as 'SNOWFLAKE.CORTEX.COMPLETE and 'SNOWFLAKE.CORTEX.CLASSIFY_TEXT , the role used by the developer must be granted the 'SNOWFLAKE.CORTEX_USER database role. This role provides the necessary permissions to call these specific AI functions. Additionally, for a Streamlit application to run and perform operations within a designated database and schema (e.g., accessing tables, stages, or storing outputs), the role requires the 'USAGE privilege on that database and schema. Option B ('CREATE SNOWFLAKE.ML.DOCUMENT INTELLIGENCE') is a privilege specifically for creating DocumentAI model builds, not for using general Cortex LLM functions. Option D (EXECUTE TASK) is required for creating and running tasks, typically in automated data pipelines, which is distinct from direct LLM function execution within a Streamlit app. Option E is an application role necessary for AI Observability to log and view application traces for debugging and performance evaluation, but it is not a core requirement for merely executing LLM functions.

302. Frage
A development team is preparing to deploy a new Retrieval-Augmented Generation (RAG) application written in Python. They intend to use Snowflake AI Observability with the TruLens SDK to capture detailed logs and traces for debugging and performance analysis. Which of the following configurations are essential prerequisites for enabling this logging capability effectively?

  • A. Option E
  • B. Option A
  • C. Option B
  • D. Option D
  • E. Option C
Antwort: A,B,C,E
Begründung:


303. Frage
......
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Posted at yesterday 01:49        Only Author  2#
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