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Snowflake GES-C01 Exam Syllabus Topics:

Snowflake SnowPro® Specialty: Gen AI Certification Sample Questions:

1.
After resolving this, they try to process a batch of 1500 documents in a single query using the method, which also fails. Which two issues are most likely contributing to these failures?

A) The batch of documents exceeds Document AI's limit of 1000 documents per query.
B) The has not been granted the 'CREATE STREAM' privilege on the
C) The 'SNOWFLAKE.DOCUMENT INTELLIGENCE CREATOR database role or the 'CREATE SNOWFLAKE.ML.DOCUMENT INTELLIGENCE' privilege on the schema has not been granted to the .
D) The name is not unique within the .
E) The virtual warehouse being used for Document AI is not a Snowpark-optimized warehouse.

2. A data application developer, adhering to Snowflake's Gen AI best practices for deploying LLMs, needs to perform inference with a newly fine-tuned llama3.1-70b model via AI_COMPLETE and expects a structured JSON output. Which of the following statements accurately describe how to configure this inference and potential limitations within Snowflake Cortex?

A) Option E
B) Option A
C) Option B
D) Option D
E) Option C

3. A data engineer is tasked with implementing a product recommendation system in Snowflake. They have pre-computed product embeddings and want to find similar items using VECTOR_COSINE_SIMILARITY They are evaluating options for interacting with this function. Which of the following statements is TRUE regarding the use of VECTOR_COSINE_SIMILARITY and Snowflake's VECTOR data type?

A) The

B) Direct comparison operators like

C) A column defined as

D) The maximum dimension supported by the

E)

4. 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

5. A data engineering team is building an automated pipeline within Snowflake to process newly ingested documents. This pipeline needs to classify each document's sentiment (positive, neutral, negative) and summarise its content using Cortex LLM functions, then store the results in a table. The pipeline is orchestrated using Streams and Tasks. Which considerations are paramount for implementing and monitoring this AI-infused data pipeline?

A) Option E
B) Option A
C) Option B
D) Option D
E) Option C

Solutions: