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Free CERTIFIED-GENERATIVE-AI-ENGINEER-ASSOCIATE – Databricks CERTIFIED-GENERATIVE-AI-ENGINEER-ASSOCIATE Practice Test Question

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Showing 1–3 of 10 questions

Question 1 (Topic 1)

A Generative Al Engineer is tasked with improving the RAG quality by addressing its inflammatory outputs. Which action would be most effective in mitigating the problem of offensive text outputs?

Select an option, then click Submit answer.

  • ○ Increase the frequency of upstream data updates
  • ○ Inform the user of the expected RAG behavior
  • ○ Restrict access to the data sources to a limited number of users
  • ○ Curate upstream data properly that includes manual review before it is fed into the RAG system
Question 2 (Topic 1)

A Generative Al Engineer has successfully ingested unstructured documents and chunked them by document sections. They would like to store the chunks in a Vector Search index. The current format of the dataframe has two columns: (i) original document file name (ii) an array of text chunks for each document. What is the most performant way to store this dataframe?

Select an option, then click Submit answer.

  • ○ Split the data into train and test set, create a unique identifier for each document, then save to a Delta table
  • ○ Flatten the dataframe to one chunk per row, create a unique identifier for each row, and save to a Delta table
  • ○ First create a unique identifier for each document, then save to a Delta table
  • ○ Store each chunk as an independent JSON file in Unity Catalog Volume. For each JSON file, the key is the document section name and the value is the array of text chunks for that section
Question 3 (Topic 1)

A Generative AI Engineer received the following business requirements for an external chatbot. The chatbot needs to know what types of questions the user asks and routes to appropriate models to answer the questions. For example, the user might ask about upcoming event details. Another user might ask about purchasing tickets for a particular event. What is an ideal workflow for such a chatbot?

Select an option, then click Submit answer.

  • ○ The chatbot should only look at previous event information
  • ○ There should be two different chatbots handling different types of user queries.
  • ○ The chatbot should be implemented as a multi-step LLM workflow. First, identify the type of question asked, then route the question to the appropriate model. If it’s an upcoming event question, send the query to a text-to-SQL model. If it’s about ticket purchasing, the customer should be redirected to a payment platform.
  • ○ The chatbot should only process payments