Master the Oracle Cloud Infrastructure 2025 Data Science Professional exam with our comprehensive Q&A collection. Review questions by topic, understand explanations, and build confidence for exam day.
Strategies to help you tackle Oracle Cloud Infrastructure 2025 Data Science Professional exam questions effectively
Allocate roughly 1-2 minutes per question. Flag difficult questions and return to them later.
Pay attention to keywords like 'MOST', 'LEAST', 'NOT', and 'EXCEPT' in questions.
Use elimination to narrow down choices. Often 1-2 options can be quickly ruled out.
Focus on understanding why answers are correct, not just memorizing facts.
Review Q&A organized by exam domains to focus your study
30% of exam • 3 questions
What is the primary purpose of OCI Data Science Service in Data & Analytics?
OCI Data Science Service serves as a fundamental component in Data & Analytics, providing essential capabilities for managing, configuring, and optimizing Oracle solutions. Understanding this domain is crucial for the Oracle Cloud Infrastructure 2025 Data Science Professional certification.
Which best practice should be followed when implementing OCI Data Science Service?
When implementing OCI Data Science Service, follow the principle of least privilege, ensure proper documentation, implement monitoring and logging, and regularly review configurations. These practices help maintain security and operational excellence.
How does OCI Data Science Service integrate with other Oracle services?
OCI Data Science Service integrates seamlessly with other Oracle services through APIs, shared authentication, and native connectors. This integration enables comprehensive solutions that leverage multiple services for optimal results.
25% of exam • 3 questions
What is the primary purpose of Machine Learning Model Development in Data & Analytics?
Machine Learning Model Development serves as a fundamental component in Data & Analytics, providing essential capabilities for managing, configuring, and optimizing Oracle solutions. Understanding this domain is crucial for the Oracle Cloud Infrastructure 2025 Data Science Professional certification.
Which best practice should be followed when implementing Machine Learning Model Development?
When implementing Machine Learning Model Development, follow the principle of least privilege, ensure proper documentation, implement monitoring and logging, and regularly review configurations. These practices help maintain security and operational excellence.
How does Machine Learning Model Development integrate with other Oracle services?
Machine Learning Model Development integrates seamlessly with other Oracle services through APIs, shared authentication, and native connectors. This integration enables comprehensive solutions that leverage multiple services for optimal results.
25% of exam • 3 questions
What is the primary purpose of Model Deployment and Management in Data & Analytics?
Model Deployment and Management serves as a fundamental component in Data & Analytics, providing essential capabilities for managing, configuring, and optimizing Oracle solutions. Understanding this domain is crucial for the Oracle Cloud Infrastructure 2025 Data Science Professional certification.
Which best practice should be followed when implementing Model Deployment and Management?
When implementing Model Deployment and Management, follow the principle of least privilege, ensure proper documentation, implement monitoring and logging, and regularly review configurations. These practices help maintain security and operational excellence.
How does Model Deployment and Management integrate with other Oracle services?
Model Deployment and Management integrates seamlessly with other Oracle services through APIs, shared authentication, and native connectors. This integration enables comprehensive solutions that leverage multiple services for optimal results.
20% of exam • 3 questions
What is the primary purpose of Data Engineering and MLOps in Data & Analytics?
Data Engineering and MLOps serves as a fundamental component in Data & Analytics, providing essential capabilities for managing, configuring, and optimizing Oracle solutions. Understanding this domain is crucial for the Oracle Cloud Infrastructure 2025 Data Science Professional certification.
Which best practice should be followed when implementing Data Engineering and MLOps?
When implementing Data Engineering and MLOps, follow the principle of least privilege, ensure proper documentation, implement monitoring and logging, and regularly review configurations. These practices help maintain security and operational excellence.
How does Data Engineering and MLOps integrate with other Oracle services?
Data Engineering and MLOps integrates seamlessly with other Oracle services through APIs, shared authentication, and native connectors. This integration enables comprehensive solutions that leverage multiple services for optimal results.
After reviewing these questions and answers, challenge yourself with our interactive practice exams. Track your progress and identify areas for improvement.
Common questions about the exam format and questions
The Oracle Cloud Infrastructure 2025 Data Science Professional exam typically contains 50-65 questions. The exact number may vary, and not all questions may be scored as some are used for statistical purposes.
The exam includes multiple choice (single answer), multiple response (multiple correct answers), and scenario-based questions. Some questions may include diagrams or code snippets that you need to analyze.
Questions are weighted based on the exam domain weights. Topics with higher percentages have more questions. Focus your study time proportionally on domains with higher weights.
Yes, most certification exams allow you to flag questions for review and return to them before submitting. Use this feature strategically for difficult questions.
Practice questions are designed to match the style, difficulty, and topic coverage of the real exam. While exact questions won't appear, the concepts and question formats will be similar.
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