[Q52-Q74] Pass 1z0-1110-25 Exam in First Attempt Guaranteed 2025 Dumps!

Rate this post

Pass 1z0-1110-25 Exam in First Attempt Guaranteed 2025 Dumps!

1z0-1110-25 Dumps Full Questions – Exam Study Guide

Oracle 1z0-1110-25 Exam Syllabus Topics:

Topic	Details
Topic 1	Apply MLOps Practices: This domain targets the skills of Cloud Data Scientists and focuses on applying MLOps within the OCI ecosystem. It covers the architecture of OCI MLOps, managing custom jobs, leveraging autoscaling for deployed models, monitoring, logging, and automating ML workflows using pipelines to ensure scalable and production-ready deployments.
Topic 2	OCI Data Science – Introduction & Configuration: This section of the exam measures the skills of Machine Learning Engineers and covers foundational concepts of Oracle Cloud Infrastructure (OCI) Data Science. It includes an overview of the platform, its architecture, and the capabilities offered by the Accelerated Data Science (ADS) SDK. It also addresses the initial configuration of tenancy and workspace setup to begin data science operations in OCI.
Topic 3	Create and Manage Projects and Notebook Sessions: This part assesses the skills of Cloud Data Scientists and focuses on setting up and managing projects and notebook sessions within OCI Data Science. It also covers managing Conda environments, integrating OCI Vault for credentials, using Git-based repositories for source code control, and organizing your development environment to support streamlined collaboration and reproducibility.
Topic 4	Implement End-to-End Machine Learning Lifecycle: This section evaluates the abilities of Machine Learning Engineers and includes an end-to-end walkthrough of the ML lifecycle within OCI. It involves data acquisition from various sources, data preparation, visualization, profiling, model building with open-source libraries, Oracle AutoML, model evaluation, interpretability with global and local explanations, and deployment using the model catalog.
Topic 5	Use Related OCI Services: This final section measures the competence of Machine Learning Engineers in utilizing OCI-integrated services to enhance data science capabilities. It includes creating Spark applications through OCI Data Flow, utilizing the OCI Open Data Service, and integrating other tools to optimize data handling and model execution workflows.

NEW QUESTION 52
You are a data scientist using Oracle AutoML to produce a model and you are evaluating the score metric for the model. Which of the following TWO prevailing metrics would you use for evaluating a multiclass classification model?

Recall

Mean squared error

F1 Score

R-Squared

Explained variance score

NEW QUESTION 53
Which is NOT a valid OCI Data Science notebook session approach?

Ensure you don’t execute long-running Python processes in a notebook cell

Run the process directly in the terminal and use Python logging to get updates on the progress of your job

Avoid having multiple users in the same notebook session due to the possibility of resource contention and write conflicts

While connecting to data in OCI Object Storage from your notebook session, the best practice is to make a local copy on the device and then upload it to your notebook session block volume

Authenticate using your notebook session’s resource principal to access other OCI resources. Resource principals provide a more secure way to authenticate to resources compared to the OCI configuration and API approach

NEW QUESTION 54
You have just completed analyzing a set of images by using Oracle Cloud Infrastructure (OCI) Data Labeling, and you want to export the annotated data. Which TWO formats are supported?

CONLL V2003

COCO

Data Labeling Service Proprietary JSON

Spacy

NEW QUESTION 55
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.

NEW QUESTION 56
You realize that your model deployment is about to reach its utilization limit. What would you do to avoid the issue before requests start to fail? Pick THREE.

Update the deployment to add more instances

Delete the deployment

Update the deployment to use fewer instances

Update the deployment to use a larger virtual machine (more CPUs/memory)

Reduce the load balancer bandwidth limit so that fewer requests come in

NEW QUESTION 57
Six months ago, you created and deployed a model that predicts customer churn for a call centre. Initially, it was yielding quality predictions. However, over the last two months, users are questioning the credibility of the predictions. Which TWO methods would you employ to verify the accuracy of the model?

Retrain the model

Validate the model using recent data

Drift monitoring

Redeploy the model

Operational monitoring

NEW QUESTION 58
Which of the following best describes the principal goal of data science?

To collect and archive exhaustive datasets from various source systems for corporate record-keeping uses.

To mine and analyze large amounts of data in order to uncover information that can be used for operational improvements and business gains.

To collect and prepare data for use as part of analytics applications.

Data science is focused on output of the analysis.

NEW QUESTION 59
You want to write a program that performs document analysis tasks such as extracting text and tables from a document. Which Oracle AI service would you use?

OCI Language

Oracle Digital Assistant

OCI Speech

OCI Vision

NEW QUESTION 60
Which components are a part of the OCI Identity and Access Management service?

Policies

Regional subnets

Compute instances

VCN

NEW QUESTION 61
You want to create an anomaly detection model using the OCI Anomaly Detection service that avoids as many false alarms as possible. False Alarm Probability (FAP) indicates model performance. How would you set the value of the False Alarm Probability?

High

Low

Zero

Use a function

NEW QUESTION 62
Which statement accurately describes an aspect of machine learning models?

Model performance degrades over time due to changes in data.

Static predictions become increasingly accurate over time.

Data models are more static and generally require fewer updates than software code.

A high-quality model will not need to be retrained as new information is received.

NEW QUESTION 63
Which of these protects customer data at rest and in transit in a way that allows customers to meet their security and compliance requirements for cryptographic algorithms and key management?

Security controls

Customer isolation

Data encryption

Identity Federation

NEW QUESTION 64
You are working as a data scientist for a healthcare company. They decide to analyze the data to find patterns in a large volume of electronic medical records. You are asked to build a PySpark solution to analyze these records in a JupyterLab notebook. What is the order of recommended stepsto develop a PySpark application in Oracle Cloud Infrastructure (OCI) Data Science?

Install a Spark conda environment, configure core-site.xml, launch a notebook session, create a Data Flow application with the Accelerated Data Science (ADS) SDK, develop your PySpark application

Configure core-site.xml, install a PySpark conda environment, create a Data Flow application with the Accelerated Data Science (ADS) SDK, develop your PySpark application, launch a notebook session

Launch a notebook session, configure core-site.xml, install a PySpark conda environment, develop your PySpark application, create a Data Flow application with the Accelerated Data Science (ADS) SDK

Launch a notebook session, install a PySpark conda environment, configure core-site.xml, develop your PySpark application, create a Data Flow application with the Accelerated Data Science (ADS) SDK

NEW QUESTION 65
Which CLI command allows the customized conda environment to be shared with co-workers?

odsc conda clone

odsc conda publish

odsc conda modify

odsc conda install

NEW QUESTION 66
You are a data scientist working for a utilities company. You have developed an algorithm that detects anomalies from a utility reader in the grid. The size of the model artifact is about 2 GB, and you are trying to store it in the model catalog. Which THREE interfaces could you use to save the model artifact into the model catalog?

OCI Python SDK

Console

Oracle Cloud Infrastructure (OCI) Command Line Interface (CLI)

Git CLI

ODSC CLI

Accelerated Data Science (ADS) Software Development Kit (SDK)

NEW QUESTION 67
You have just started as a data scientist at a healthcare company. You have been asked to analyze and improve a deep neural network model, which was built based on the electrocardiogram records of patients.
There are no details about the model framework that was built. What would be the best way to find more details about the machine learning models inside the model catalog?

Refer to the code inside the model

Check for model taxonomy details

Check for metadata tags

Check for provenance details

Detailed Answer in Step-by-Step Solution:
* Context Analysis: You need to investigate an existing deep neural network model in the OCI Model Catalog with no prior information.
* Understand Model Catalog: The Model Catalog stores trained models along with metadata, hyperparameters, and provenance (origin and history) details.
* Evaluate Options:
* A. Refer to the code inside the model: The model artifact (e.g., a serialized file like .pkl) doesn’t typically include readable source code; it’s a trained object, not the training script.
* B. Check for model taxonomy details: Taxonomy (e.g., classification vs. regression) provides high-level categorization but lacks specifics like framework or architecture.
* C. Check for metadata tags: Metadata includes name, description, and tags, offering some context but not detailed framework info (e.g., TensorFlow vs. PyTorch).
* D. Check for provenance details: Provenance tracks the model’s creation process, including the framework, training environment, and data sources, providing the most comprehensive insight.
* Reasoning: Provenance details are designed to document the “how” and “what” of model creation, making them ideal for uncovering the framework (e.g., Keras, PyTorch) and other specifics absent from initial handover.
* Conclusion: D is the best approach for detailed investigation.
In OCI Data Science, the Model Catalog stores provenance information, which includes “details about the model’s origin, such as the framework used (e.g., TensorFlow, PyTorch), the training environment, and dataset references.” This is more informative than metadata tags (C), which are user-defined and less structured, or taxonomy (B), which is broad. The model artifact (A) is a binary file (e.g., pickle), not a readable codebase. Provenance (D) offers a detailed audit trail, critical for analyzing an undocumented deep neural network model like this one.
Oracle Cloud Infrastructure Data Science Documentation, “Model Catalog – Provenance Details” section.

NEW QUESTION 68
As a data scientist, you are trying to automate a machine learning (ML) workflow and have decided to use Oracle Cloud Infrastructure (OCI) AutoML Pipeline. Which THREE are part of the AutoML Pipeline?

Feature Selection

Adaptive Sampling

Model Deployment

Feature Extraction

Algorithm Selection

NEW QUESTION 69
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?

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

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

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

Deactivate your notebook session, provision a new notebook session on a larger compute shapeand re- create all of your file changes

NEW QUESTION 70
You are a data scientist leveraging the Oracle Cloud Infrastructure (OCI) Language AI service for various types of text analyses. Which TWO capabilities can you utilize with this tool?

Table extraction

Punctuation correction

Sentence diagramming

Topic classification

Sentiment analysis

NEW QUESTION 71
What is the first step in the data science process?

Collecting data and preparing it for analysis

Experimenting with and tuning different analytical models

Defining an analytical hypothesis that could provide business value

Working with data owners

NEW QUESTION 72
You realize that your model deployment is about to reach its utilization limit. What would you do to avoid the issue before requests start to fail? Which THREE steps would you perform?

Update the deployment to add more instances

Delete the deployment

Update the deployment to use fewer instances

Update the deployment to use a larger virtual machine (more CPUs/memory)

Reduce the load balancer bandwidth limit so that fewer requests come in

NEW QUESTION 73
You want to make your model more parsimonious to reduce the cost of collecting and processing data. You plan to do this by removing features that are highly correlated. You would like to create a heatmap that displays the correlation so that you can identify candidate features to remove. Which Accelerated Data Science (ADS) SDK method would be appropriate to display the correlation between Continuous and Categorical features?

corr()

correlation_ratio_plot()

pearson_plot()

cramersv_plot()

NEW QUESTION 74
Which type of firewalls are designed to protect against web application attacks, such as SQL injection and cross-site scripting?

Stateful inspection firewall

Web Application Firewall

Incident firewall

Packet filtering firewall

Oracle Cloud Free Certification Exam Material from ActualTorrent with 160 Questions: https://www.actualtorrent.com/1z0-1110-25-questions-answers.html

[Q52-Q74] Pass 1z0-1110-25 Exam in First Attempt Guaranteed 2025 Dumps!

Oracle 1z0-1110-25 Exam Syllabus Topics:

Be the first to reply

Leave a Reply Cancel reply

Oracle 1z0-1110-25 Exam Syllabus Topics: