1.
Question 1
Question prompt: What is the primary purpose of Spark Notebooks within the Databricks platform?


Version control



Data exploration and collaboration



Data visualization



Automated model deployment


1 point
2.
Question 2

Question prompt: Which of the following is a feature of Databricks workspaces?


Advanced modeling capabilities



Creating and sharing notebooks



Running MLFlow



Both a and b


1 point
3.
Question 3

Question prompt: How can Databricks be used in connection with AutoML workflows?


Using the DBFS



Registering models



Exploring Azure Features



All of the above


1 point
4.
Question 4
Question prompt: What does the Databricks File System (DBFS) primarily enable users to do?


Run PySpark



Store and manage data within Databricks



Deploy models



Register models


1 point
5.
Question 5

Question prompt: What is one primary advantage of using PySpark on Databricks?


Custom-built language



Integration with DBFS



Ability to process large-scale data



Model registration feature


1 point
6.
Question 6

Question prompt: What is the primary purpose of the Databricks model registry?


Data visualization



Managing the full lifecycle of ML models



AutoML workflows



Running PySpark jobs


1 point
7.
Question 7

Question prompt: What is Azure Databricks mainly designed to facilitate?


Mobile app development



Big data analytics and collaborative data science



Software version control



Web hosting


1 point
8.
Question 8

Question prompt: What is one of the main purposes of integrating MLFlow with Databricks?


Real-time communication



User authentication



Managing and tracking ML experiments



Web development


1 point
9.
Question 9

Question prompt: Which of the following represents an advanced capability of Databricks?


Basic data storage



Serverless Compute



Simple data visualization



General model registration


1 point
10.
Question 10

Question prompt: What is one of the primary prerequisites for starting with Databricks ML and MLOps?


Knowing a specific programming language



Having a physical server setup



Understanding the fundamentals of machine learning and data processing



Owning specific hardware


1 point
11.
Question 11

Question prompt: Which of the following best describes the function of PySpark within the context of Databricks?


A web development framework



A distributed data processing framework



A database management system



A machine learning model registry


1 point
12.
Question 12

Question prompt: What is a significant benefit of using open-source MLFlow in Databricks?


Creating user interfaces



Experiment tracking and model deployment



Managing user permissions



Hosting web applications


1 point
13.
Question 13

Question prompt: Which of the following is a reason to explore Databricks Azure features?


Learning a new programming language



Building mobile applications



Collaborative big data analysis and integration with Azure services



Designing graphics


1 point
14.
Question 14

Question prompt: What is a key advantage of implementing an end-to-end machine learning solution using Databricks and MLFlow?


Developing mobile apps



Building websites



Streamlined model development, tracking, and deployment



Creating video games


1 point