Prep and try our GES-C01 valid and latest training questions & answers

Snowflake GES-C01 Exam Overview:

Snowflake GES-C01 Exam Syllabus Topics:

Snowflake SnowPro® Specialty: Gen AI Certification Sample Questions:

1. A data science team is fine-tuning a Snowflake Document AI model to improve the extraction accuracy of specific fields from a new type of complex legal document. They are consistently observing low confidence scores and inconsistent 'value' keys for extracted entities, even after initial training. Which two of the following best practices should the team follow to most effectively improve the model's extraction accuracy and confidence for this complex document type?

A) Prioritize extensive prompt engineering by creating highly detailed and complex questions with intricate logic to guide the LLM's understanding of the extraction task.
B) Set the 'temperature' parameter to a higher value (e.g., 0.7) during '!PREDICT calls to encourage more creative and diverse interpretations by the model.
C) Limit the fine-tuning training data exclusively to perfectly formatted and clean documents to ensure the model learns from ideal examples without noise.
D) Actively involve subject matter experts (SMEs) or document owners throughout the iterative process to help define data values, provide annotations, and evaluate the model's effectiveness.
E) Ensure the training dataset used for fine-tuning includes diverse documents representing various layouts, data variations, and explicit examples of values or empty cells where appropriate.

2. A data engineer is configuring a Document AI pipeline to process scanned PDF invoices stored in an internal stage named 'invoice_docs_stage'. After uploading the PDF files, they execute an extracting query using '!PREDICT. The query consistently returns the error:

Which of the following is the most likely cause of this error?

A) The PDF documents exceed the maximum allowed file size of 50 MB.
B) The documents contain non-English text, which is not fully supported by Document AI for optimal results.
C) The internal stage was not created with 'SNOWFLAKE_SSE' encryption enabled.
D) The Document AI model build is attempting to process more than 1000 documents in a single query.
E) The 'GET_PRESIGNED_URL' function used in the '!PREDICT query has an expired URL.

3. A Data Engineer is responsible for deploying machine learning models using Snowpark Container Services. They need to ensure that a specific role, model_deployer_role, has the appropriate permissions to create a Snowpark Container Service that uses an image from an existing image repository named my_inferenc_ images. Which of the following SQL commands grant the necessary privileges 'on the image repository' for this purpose?

A)

B)

C)

D)

E)

4. A data engineering team is preparing a large corpus of unstructured text documents for a Retrieval Augmented Generation (RAG) application in Snowflake, leveraging Cortex Search and LLM functions. They plan to use SNOWFLAKE.CORTEX.SPLIT_TEXT_RECURSIVE_CHARACTER as part of their data ingestion pipeline. What is the primary benefit of employing this helper function in the context of their RAG workflow?

A) It generates vector embeddings for each document chunk, eliminating the need for separate embedding models.
B) It automatically translates documents into a target language, ensuring multilingual compatibility for the LLM.
C) It divides lengthy documents into smaller, manageable text chunks, which improves the precision of information retrieval and the relevance of downstream LLM responses.
D) It compresses the text data to reduce storage costs in Snowflake stages before processing by embedding models.
E) It performs sentiment analysis on each chunk, allowing the RAG system to filter out negative or irrelevant content before retrieval.

5. 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 provides a built-in retry mechanism for LLM calls that encounter temporary failures, automatically re-submitting the prompt up to three times.
B) It offers enhanced security features, such as automatic input sanitization, which are not available in the standard
C) It returns
D) It processes tokens at a significantly reduced rate compared to
E) It automatically adjusts the LLM's

Solutions: