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Oracle 1z0-1110-25 Exam Syllabus Topics:

Topic	Details
Topic 1	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.
Topic 2	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 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	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 5	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.

Oracle Cloud Infrastructure 2025 Data Science Professional Sample Questions (Q45-Q50):

NEW QUESTION # 45
Which Oracle Cloud Infrastructure (OCI) Data Science policy is invalid?

A. Allow dynamic-group DataScienceDynamicGroup to manage data-science-projects in compartment DataScience
B. Allow group DataScienceGroup to use data-science-model-sessions in compartment DataScience
C. Allow group DataScienceGroup to use virtual-network-family in compartment DataScience
D. Allow dynamic-group DataScienceDynamicGroup to manage data-science-family in compartment DataScience

Answer: B

Explanation:
Detailed Answer in Step-by-Step Solution:
* Objective: Spot the invalid OCI IAM policy.
* Understand Policies: Use verbs (e.g., use, manage) and resource types.
* Evaluate Options:
* A: Valid-virtual-network-family is a resource type.
* B: Invalid-No data-science-model-sessions resource type; likely meant data-science-models.
* C: Valid-data-science-projects is correct.
* D: Valid-data-science-family aggregates Data Science resources.
* Reasoning: B uses a nonexistent resource type-error in syntax.
* Conclusion: B is incorrect.
OCI IAM documentation lists valid resource types: "data-science-models, data-science-projects, data-science- family-but not data-science-model-sessions (B)." A, C, D are correct-B is invalid due to this typo
/misunderstanding.
Oracle Cloud Infrastructure IAM Documentation, "Data Science Resource Types".

NEW QUESTION # 46
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?

A. CONLL V2003
B. Spacy
C. Data Labeling Service Proprietary JSON
D. COCO

Answer: C,D

Explanation:
Detailed Answer in Step-by-Step Solution:
* Objective: Identify export formats for OCI Data Labeling.
* Understand Export: Annotated data is exported for ML use.
* Evaluate Options:
* A: CONLL V2003-Text-specific, not OCI-supported.
* B: COCO-Standard for image annotations-correct.
* C: Proprietary JSON-OCI's default format-correct.
* D: Spacy-NLP format, not supported.
* Reasoning: B and C are image-compatible per OCI docs.
* Conclusion: B and C are correct.
OCI documentation states: "Data Labeling exports annotations in COCO format (B) for image tasks and a proprietary JSON format (C) specific to the service." CONLL (A) and Spacy (D) are text/NLP-focused-not supported for OCI's image annotations.
Oracle Cloud Infrastructure Data Labeling Documentation, "Export Formats".

NEW QUESTION # 47
You have been given a collection of digital files required for a business audit. They consist of several different formats that you would like to annotate using Oracle Cloud Infrastructure (OCI) Data Labeling.
Which THREE types of files could this tool annotate?

A. A collection of purchase orders for office supplies
B. Images of computer server racks
C. An audio recording of a phone conversation
D. A typewritten document that details an annual budget
E. Video footage of a conversation in a conference room

Answer: B,D,E

Explanation:
Detailed Answer in Step-by-Step Solution:
* Understand OCI Data Labeling Capabilities: OCI Data Labeling is designed to annotate data for machine learning, supporting specific file types like images, text documents, and videos.
* Evaluate Options:
* A. Video footage: Supported for tasks like object detection or action recognition.
* B. Images: Supported for image classification, object detection, etc.
* C. Typewritten document: Supported as text data for tasks like entity extraction or classification.
* D. Purchase orders: While potentially text-based, this is ambiguous without format clarification (e.g., PDF, image). OCI supports text annotation, but "purchase orders" isn't a specific file type- it's assumed as text here.
* E. Audio recording: Not supported, as OCI Data Labeling focuses on visual and textual data, not audio.
* Select Three: A (video), B (images), and C (text documents) are explicitly supported file types.
OCI Data Labeling supports annotating datasets of images, text, and videos, as per the official documentation.
Video footage (A) can be annotated for tasks like object tracking, images (B) for classification or detection, and typewritten documents (C) for text-based annotations (e.g., named entity recognition). Audio files (E) are not supported, and while purchase orders (D) could be text, the question specifies "typewritten document" as a clearer match. (Reference: Oracle Cloud Infrastructure Data Labeling Service Documentation, "Supported Data Types").

NEW QUESTION # 48
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?

A. OCI Speech
B. OCI Language
C. OCI Vision
D. Oracle Digital Assistant

Answer: C

Explanation:
Detailed Answer in Step-by-Step Solution:
* Objective: Select an OCI AI service for text and table extraction from documents.
* Evaluate Options:
* A: Language-Text analysis, not extraction-incorrect.
* B: Digital Assistant-Chatbots, not document tasks-incorrect.
* C: Speech-Audio transcription, not documents-incorrect.
* D: Vision-OCR for text/tables-correct.
* Reasoning: Vision's OCR extracts text and tables from document images.
* Conclusion: D is correct.
OCI documentation states: "OCI Vision (D) uses OCR to extract text and tables from documents, supporting document analysis tasks." A analyzes text post-extraction, B and C are unrelated-only D fits per OCI's AI services.
Oracle Cloud Infrastructure Vision Documentation, "Document Analysis Features".

NEW QUESTION # 49
Which architecture is based on the principle of "never trust, always verify"?

A. Zero trust
B. Fluid perimeter
C. Defense in depth
D. Federated identity

Answer: A

Explanation:
Detailed Answer in Step-by-Step Solution:
* Objective: Identify the architecture with "never trust, always verify."
* Evaluate Options:
* A: Federated identity-Shares auth, not verification-focused.
* B: Zero trust-Explicitly "never trust, always verify"-correct.
* C: Fluid perimeter-Adaptive, not the core principle.
* D: Defense in depth-Layered, not verification-centric.
* Reasoning: Zero trust matches the stated principle exactly.
* Conclusion: B is correct.
OCI documentation states: "Zero trust (B) architecture operates on 'never trust, always verify,' requiring continuous authentication and authorization." A, C, and D have different focuses-only B aligns with OCI's security philosophy.
Oracle Cloud Infrastructure Security Documentation, "Zero Trust Architecture".

NEW QUESTION # 50
......

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Study 1z0-1110-25 Test, Reliable 1z0-1110-25 Practice Materials

100% Pass 2025 Oracle 1z0-1110-25: Oracle Cloud Infrastructure 2025 Data Science Professional Pass-Sure Study Test

Oracle 1z0-1110-25 Exam Syllabus Topics:

Oracle Cloud Infrastructure 2025 Data Science Professional Sample Questions (Q45-Q50):

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