[Q65-Q82] 1z0-1110-25 100% Guarantee Download 1z0-1110-25 Exam PDF Q&A [Apr 11, 2026]

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1z0-1110-25 100% Guarantee Download 1z0-1110-25 Exam PDF Q&A [Apr 11, 2026]

Get 1z0-1110-25 Actual Free Exam Q&As to Prepare for Your Oracle Certification

Q65. On which option do you set Oracle Cloud Infrastructure Budget?

Compartments

Instances

Free-form tags

Tenancy

Q66. Which Oracle Cloud Service provides restricted access to target resources?

Bastion

Internet Gateway

Load Balancer

SSL Certificate

Q67. You are attempting to save a model from a notebook session to the model catalog by using ADS SDK, with resource principal as the authentication signer, and you get a 404 authentication error. Which TWO should you look for to ensure permissions are set up correctly?

The dynamic groups matching rule exists for notebook sessions in the compartment

The model artifact is saved to the block volume of the notebook session

The policy for the dynamic group grants manage permissions for the model catalog in this compartment

The networking configuration allows access to the Oracle Cloud Infrastructure services through a service gateway

The policy for your user group grants manage permissions for the model catalog in this compartment

Q68. Why is data sampling useful for data scientists?

It lets them analyze datasets in small batches to reduce their use of system resources.

It reduces the amount of data storage space that’s required for data science applications.

It enables them to use a representative subset of data to build accurate analytical models more quickly.

Q69. You loaded data into Oracle Cloud Infrastructure (OCI) Data Science. To transform the data, you want to use the Accelerated Data Science (ADS) SDK. When you applied the get_recommendations() tool to the ADSDataset object, it showed you user-detected issues with all the recommended changes to apply to the dataset. Which option should you use to apply all the recommended transformations at once?

get_transformed_dataset()

fit_transform()

auto_transform()

visualize_transforms()

Q70. You are a data scientist leveraging Oracle Cloud Infrastructure (OCI) Data Science to create a model and need some additional Python libraries for processing genome sequencing data. Which of the following THREE statements are correct with respect to installing additional Python libraries to process the data?

You can only install libraries using yum and pip as a normal user

You can install private or custom libraries from your own internal repositories

OCI Data Science allows root privileges in notebook sessions

You can install any open-source package available on a publicly accessible Python Package Index (PyPI) repository

You cannot install a library that’s not preinstalled in the provided image

Q71. What is a common maxim about data scientists?

They spend 80% of their time finding and preparing data and 20% analyzing it.

They spend 80% of their time analyzing data and 20% finding and preparing it.

They spend 80% of their time on failed analytics projects and 20% doing useful work.

Q72. Which statement about logs for Oracle Cloud Infrastructure Jobs is true?

Each job run sends outputs to a single log for that job

Integrating data science jobs resources with logging is mandatory

All stdout and stderr are automatically stored when automatic log creation is enabled

Logs are automatically deleted when the job and job run is deleted

Q73. You are using Oracle Cloud Infrastructure (OCI) Anomaly Detection to train a model to detect anomalies in pump sensor data. How does the required False Alarm Probability setting affect an anomaly detection model?

It is used to disable the reporting of false alarms

It changes the sensitivity of the model to detecting anomalies

It determines how many false alarms occur before an error message is generated

It adds a score to each signal indicating the probability that it’s a false alarm

Q74. Which TWO statements about Oracle Cloud Infrastructure (OCI) Open Data service are true?

Open Data includes text and image data repositories for AI and ML.

Audio and video formats are not available.

Each dataset in Open Data consists of code and tooling usage examples for consumption and reproducibility.

Open Data is a dataset repository made for the people that create, use, and manipulate datasets.

A primary goal of Open Data is for users to contribute to the data repositories to expand the content offered.

Subscribers can pay and log into Open Data to view curated datasets that are otherwise not available to the public.

Q75. As a data scientist, you are working on a global health dataset that has data from more than 50 countries. You want to encode three features, such as ‘countries’, ‘race’, and ‘body organ’ as categories. Which option would you use to encode the categorical feature?

DataFrameLabelEncode()

auto_transform()

OneHotEncoder()

show_in_notebook()

Q76. Where do calls to stdout and stderr from score.py go in the model deployment?

The file that was defined for them on the virtual machine (VM)

The OCI Console

The OCI Cloud Shell, which can be accessed from the console

The predict log in the Oracle Cloud Infrastructure (OCI) Logging service as defined in the deployment

Q77. Which OCI cloud service lets you centrally manage the encryption keys that protect your data and the secret credentials that you use to securely access resources?

Data Safe

Cloud Guard

Data Guard

Vault

Q78. Which Oracle Cloud Infrastructure (OCI) Data Science policy is invalid?

Allow group DataScienceGroup to use virtual-network-family in compartment DataScience

Allow group DataScienceGroup to use data-science-model-sessions in compartment DataScience

Allow dynamic-group DataScienceDynamicGroup to manage data-science-projects in compartment DataScience

Allow dynamic-group DataScienceDynamicGroup to manage data-science-family in compartment DataScience

Q79. You are creating an Oracle Cloud Infrastructure (OCI) Data Science job that will run on a recurring basis in a production environment. This job will pick up sensitive data from an Object Storage Bucket, train a model, and save it to the model catalog. How would you design the authentication mechanism for the job?

Create a pre-authenticated request (PAR) for the Object Storage bucket and use that in the job code

Use the resource principal of the job run as the signer in the job code, ensuring there is a dynamic group for this job run with appropriate access to Object Storage and the model catalog

Package your personal OCI config file and keys in the job artifact

Store your personal OCI config file and keys in the Vault, and access the Vault through the job run resource principal

Q80. True or false? Bias is a common problem in data science applications.

True

False

Q81. You have received machine learning model training code, without clear information about the optimal shape to run the training. How would you proceed to identify the optimal compute shape for your model training that provides a balanced cost and processing time?

Start with a smaller shape and monitor the Job Run metrics and time required to complete the model training. If the compute shape is not fully utilized, tune the model parameters, and rerun the job. Repeat the process until the shape resources are fully utilized

Start with the strongest compute shape Jobs support and monitor the Job Run metrics and time required to complete the model training. Tune the model so that it utilizes as much compute resources as possible, even at an increased cost

Start with a smaller shape and monitor the utilization metrics and time required to complete the model training. If the compute shape is fully utilized, change to compute that has more resources and rerun the job. Repeat the process until the processing time does not improve

Start with a random compute shape and monitor the utilization metrics and time required to finish the model training. Perform model training optimizations and performance tests in advance to identify the right compute shape before running the model training as a job

Q82. Which step is a part of the AutoML pipeline?

Feature Extraction

Model saved to Model Catalog

Model Deployment

Feature Selection