A team has a set of PDF files that are a mix of scanned images and digital text. Some pages are scanned, others are digital. They need to extract text from all pages. Which approach is most efficient?

Use pdfplumber on all pages, and for pages where it returns empty, use pytesseract

After extracting text from a PDF using PyPDF2, which step is commonly performed to prepare the text for downstream NLP processing?

Convert the text to a pandas DataFrame

Clean the text by removing extra whitespace and special characters

A developer is extracting text from HTML pages that contain tables. The downstream process needs the table data in a structured format (e.g., a list of rows). Which package and method is most appropriate?

Use pdfplumber to extract the table

Use BeautifulSoup to find all ` ` tags and iterate over ` ` and ` ` elements

Use BeautifulSoup's `.get_text()` on the entire page

Use PyPDF2 to extract the table

A developer is building a RAG pipeline that ingests documents from a public website. The website serves HTML pages that are dynamically generated with JavaScript. The developer needs to extract the rendered text content. Which approach is most appropriate?

Use pdfplumber to extract the text

Use BeautifulSoup to parse the raw HTML response

Use a headless browser like Selenium or Playwright to render the page, then extract the text

DatabricksCertified Generative AI Engineer Associate

Domain 2Objective 3

Choose the Appropriate Python Package to Extract Document Content from Provided Source Data and Format. GENERATIVE-AI-ENGINEER-ASSOCIATE Practice Questions (Page 2)

Part of the Section 2: Data Preparation domain, which makes up ~25% of our current practice bank. Databricks does not publish an official question count, but from its 90-minute exam (~35–60 total, ~9–15 in this domain), expect 1–2 from this objective — we provide 21 practice questions to prepare you well beyond it. (estimate)

21questions here

5free pages

3concepts

Questions 6–10

6expert · medium
A data engineer is building a pipeline to process a mixed corpus of documents: some are `.docx`, some are `.html`, and some are scanned `.pdf` files. The pipeline must extract text from all of them, but the engineer wants to minimize the number of different libraries to learn and maintain. Which single library can handle all three formats?
Select an answer first
7expert · hard
A team has a set of PDF files that are a mix of scanned images and digital text. Some pages are scanned, others are digital. They need to extract text from all pages. Which approach is most efficient?
Select an answer first
8foundation · easy
After extracting text from a PDF using PyPDF2, which step is commonly performed to prepare the text for downstream NLP processing?
Select an answer first
9application · medium
A developer is extracting text from HTML pages that contain tables. The downstream process needs the table data in a structured format (e.g., a list of rows). Which package and method is most appropriate?
Select an answer first
10expert · hard
A developer is building a RAG pipeline that ingests documents from a public website. The website serves HTML pages that are dynamically generated with JavaScript. The developer needs to extract the rendered text content. Which approach is most appropriate?
Select an answer first

Finished these 5 questions?

Review the revealed explanations, or continue through the curriculum.

Next 5 questions →Back to GENERATIVE-AI-ENGINEER-ASSOCIATE

Free Basic Practice is a study aid with revealable answers — not a scored exam. Examers.io is independent and not affiliated with or endorsed by Databricks. “GENERATIVE-AI-ENGINEER-ASSOCIATE” is a trademark of its owner, used for identification only.