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  • Questions: 80 Q&A's
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  • Exam Name: Oracle Cloud Infrastructure Data Science 2023 Professional
  • Last Update: 03-Dec-2024
  • Questions and Answers: 80
  • Single Choice: 58 Q&A's
  • Multiple Choice: 22 Q&A's

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1z0-1110-23 Questions and Answers

Question # 1

You want to evaluate the relationship between feature values and target variables. You have a

large number of observations having a near uniform distribution and the features are highly

correlated.

Which model explanation technique should you choose?

A.

Feature Permutation Importance Explanations

B.

Local Interpretable Model-Agnostic Explanations

C.

Feature Dependence Explanations

D.

Accumulated Local Effects

Question # 2

You are a data scientist building a pipeline in the Oracle Cloud Infrastructure (OCI) Data Science

service for your machine learning project. You want to optimize the pipeline completion time by

running some steps in parallel. Which statement is true about running pipeline steps in parallel?

A.

Steps in a pipeline can be run only sequentially.

B.

Pipeline steps can be run in sequence or in parallel, as long as they create a directed acyclic

graph (DAG).

C.

All pipeline steps are always run in parallel.

D.

Parallel steps cannot be run if they are completely independent of each other.

Question # 3

As a data scientist, you have stored sensitive data in a database. You need to protect this data by

using a master encryption algorithm, which uses symmetric keys. Which master encryption

algorithm would you choose in the Oracle Cloud Infrastructure (OCI) Vault service?

A.

Triple Data Encryption Standard Algorithm

B.

Elliptical Curve Cryptography Digital Signature Algorithm

C.

Advanced Encryption Standard Keys

D.

Rivert-Shamir-Adleman Keys

Question # 4

As you are working in your notebook session, you find that your notebook session does not have

enough compute CPU and memory for your workload.

How would you scale up your notebook session without losing your work?

A.

Create a temporary bucket on Object Storage, write all your files and data to Object Storage,

delete your notebook session, provision a new notebook session on a larger compute shape,

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and copy your files and data from your temporary bucket onto your new notebook session.

B.

Ensure your files and environments are written to the block volume storage under the

/home/datascience directory, deactivate the notebook session, and activate the notebook

session with a larger compute shape selected.

C.

Download all your files and data to your local machine, delete your notebook session,

provision a new notebook session on a larger compute shape, and upload your files from

your local machine to the new notebook session.

D.

Deactivate your notebook session, provision a new notebook session on a larger compute

shape and re-create all of your file changes.

Question # 5

What preparation steps are required to access an Oracle AI service SDK from a Data Science

notebook session?

A.

Create and upload score.py and runtime.yaml.

B.

Create and upload the APIsigning key and config file.

C.

Import the REST API.

D.

Call the ADS command to enable AI integration

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