Oracle 1Z0-1110 OCI Data Science Pro Practice Exam
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Oracle 1Z0-1110 Oracle Cloud Infrastructure Data Science 2022 Professional
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Start NowAbout the Oracle 1Z0-1110 OCI Data Science Pro Certification
The Oracle 1Z0-1110 OCI Data Science Pro certification is designed for professionals who build data science workflows, train models, and deploy analytics in OCI. As technology evolves and industry demands grow more complex; this credential validates your ability to apply real-world skills and knowledge using Oracle tools and frameworks. Earning the certification positions you as a trusted expert, capable of solving high-impact challenges and contributing to secure, scalable, and efficient systems.
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Test Your Knowledge of Oracle 1Z0-1110 OCI Data Science Pro
Question #1
A data scientist wants to build a model using OCI resources.
Which feature supports this?
A) Data Science Service
B) Model Builder
C) AI Platform
D) Analytics Cloud
Solution
Correct answers: A – Explanation:
Data Science Service provides notebooks, compute, and model lifecycle tools. Others are informal or not standard Oracle features.
Question #2
An implementer needs to configure access to datasets.
Which setup supports this?
A) Object Storage Policies
B) Data Access Rule
C) Dataset Permissions
D) Storage Guard
Solution
Correct answers: A – Explanation:
Object Storage Policies define access to training data. Others are informal or not standard Oracle features.
Question #3
A user wants to monitor model training progress.
Which dashboard provides this?
A) Model Training Dashboard
B) Notebook Monitor
C) Job Tracker
D) Data Science Console
Solution
Correct answers: D – Explanation:
Data Science Console shows job status and metrics. Others are informal or not standard Oracle dashboards.
Question #4
A manager wants to restrict access to ML models.
Which configuration supports this?
A) Compartment Policies
B) Model Security
C) Access Control
D) Role-Based Access
Solution
Correct answers: D – Explanation:
Role-Based Access limits visibility. Others are informal or not standard Oracle features.
Question #5
An implementer needs to automate model deployment.
Which feature supports this?
A) Model Deployment
B) Auto Deploy
C) Deployment Pipeline
D) ML Flow
Solution
Correct answers: A – Explanation:
Model Deployment publishes models to endpoints. Others are informal or not standard Oracle features.
Question #6
A user wants to validate model accuracy.
Which tool supports this?
A) Evaluation Metrics
B) Accuracy Report
C) Model Validator
D) Performance Summary
Solution
Correct answers: A – Explanation:
Evaluation Metrics provide precision, recall, and F1 scores. Others are informal or not standard Oracle tools.
Question #7
An architect needs to integrate models with applications.
Which setup supports this?
A) Model Endpoint
B) API Gateway
C) Integration Rule
D) Analytics Cloud
Solution
Correct answers: A – Explanation:
Model Endpoint exposes models via REST. Others are informal or not standard Oracle features.
Question #8
An implementer wants to track model versions.
Which feature supports this?
A) Model Catalog
B) Version Tracker
C) Model History
D) Deployment Log
Solution
Correct answers: A – Explanation:
Data Science Service provides notebooks, compute, and model lifecycle tools. Others are informal or not standard Oracle features.
Question #9
A user wants to visualize training data.
Which tool supports this?
A) Notebook Session
B) Data Viewer
C) Training Explorer
D) Visualization Console
Solution
Correct answers: A – Explanation:
Notebook Session supports Python-based exploration. Others are informal or not standard Oracle tools.
Question #10
A manager wants to analyze data science project performance.
Which report provides this?
A) Data Science Metrics Dashboard
B) Project Summary
C) ML KPI View
D) Efficiency Report
Solution
Correct answers: A – Explanation:
Data Science Metrics Dashboard tracks job success and resource usage. Others are informal or not standard Oracle reports.
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