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Databricks-Generative-AI-Engineer-Associate Question and answers Include

Total Questions: 45 Q&A's
Single Choice: 42 Q&A's
Multiple Choice: 3 Q&A's

Databricks Databricks-Generative-AI-Engineer-Associate Exam Dumps - Valid Questions Answers

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Databricks-Generative-AI-Engineer-Associate Questions and Answers

Question # 1

A Generative Al Engineer is responsible for developing a chatbot to enable their company’s internal HelpDesk Call Center team to more quickly find related tickets and provide resolution. While creating the GenAI application work breakdown tasks for this project, they realize they need to start planning which data sources (either Unity Catalog volume or Delta table) they could choose for this application. They have collected several candidate data sources for consideration:

call_rep_history: a Delta table with primary keys representative_id, call_id. This table is maintained to calculate representatives’ call resolution from fields call_duration and call start_time.

transcript Volume: a Unity Catalog Volume of all recordings as a *.wav files, but also a text transcript as *.txt files.

call_cust_history: a Delta table with primary keys customer_id, cal1_id. This table is maintained to calculate how much internal customers use the HelpDesk to make sure that the charge back model is consistent with actual service use.

call_detail: a Delta table that includes a snapshot of all call details updated hourly. It includes root_cause and resolution fields, but those fields may be empty for calls that are still active.

maintenance_schedule – a Delta table that includes a listing of both HelpDesk application outages as well as planned upcoming maintenance downtimes.

They need sources that could add context to best identify ticket root cause and resolution.

Which TWO sources do that? (Choose two.)

A.

call_cust_history

B.

maintenance_schedule

C.

call_rep_history

D.

call_detail

E.

transcript Volume

Question # 2

A Generative AI Engineer is building a RAG application that will rely on context retrieved from source documents that are currently in PDF format. These PDFs can contain both text and images. They want to develop a solution using the least amount of lines of code.

Which Python package should be used to extract the text from the source documents?

A.

flask

B.

beautifulsoup

C.

unstructured

D.

numpy

Question # 3

A Generative Al Engineer is tasked with developing an application that is based on an open source large language model (LLM). They need a foundation LLM with a large context window.

Which model fits this need?

A.

DistilBERT

B.

MPT-30B

C.

Llama2-70B

D.

DBRX

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