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| Section | Objectives |
|---|---|
| Topic 1: Apply MLOps Practices | - Monitor and maintain machine learning models - Implement model lifecycle management - Use best practices for operationalizing ML solutions |
| Topic 2: Use Related OCI Services | - Apply OCI services for data ingestion, storage, and processing - Integrate OCI Data and AI services - Design machine learning solutions for business use cases |
| Topic 3: Design and Set Up Data Science Workspace | - Create and configure Data Science projects - Manage notebook sessions and compute resources - Use Accelerated Data Science SDK and open source tools |
| Topic 4: Implement End-to-End Machine Learning Lifecycle | - Prepare and manage datasets - Deploy models and consume model endpoints - Build, train, and evaluate machine learning models - Automate machine learning workflows and pipelines - Save and manage models using Model Catalog |
| Topic 5: OCI Data Science - Introduction and Configuration | - Understand OCI Data Science service concepts and architecture - Configure and manage Data Science resources - Use OCI Data Science notebooks and sessions |
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NEW QUESTION # 124
Which statement about resource principals is true?
Answer: C
Explanation:
Detailed Answer in Step-by-Step Solution:
Define Resource Principals: They allow OCI resources (e.g., notebook sessions) to authenticate to other OCI services without user credentials.
Evaluate Options:
A: False—Resource principals eliminate manual credential management.
B: False—They’re secure, leveraging IAM policies, not less secure than API keys.
C: False—Data Science supports resource principals for accessing resources (e.g., Object Storage).
D: True—Resource principals are an IAM feature authorizing resources as actors.
Reasoning: D captures the essence of resource principals as an IAM mechanism.
Conclusion: D is correct.
OCI documentation states: “A resource principal is an IAM feature that enables OCI resources, such as compute instances or notebook sessions, to act as principal actors and authenticate to other OCI services using policies.” This refutes A (no credentials needed), B (secure method), and C (supported in Data Science), making D the accurate statement.
1: Oracle Cloud Infrastructure IAM Documentation, "Resource Principals".
NEW QUESTION # 125
You are preparing a configuration object necessary to create a Data Flow application. Which THREE parameter values should you provide?
Answer: A,C,E
Explanation:
Detailed Answer in Step-by-Step Solution:
Objective: Identify three required params for an OCI Data Flow app config.
Understand Data Flow: Runs Spark apps; needs compartment, storage, and identity.
Evaluate Options:
A: Archive path—Optional if script is in Object Storage—incorrect.
B: Local script path—Not needed; script is uploaded—incorrect.
C: Compartment—Required for resource scope—correct.
D: Bucket—Required for script storage/access—correct.
E: Display name—Required for app identification—correct.
Reasoning: C, D, E are mandatory metadata for Data Flow creation—script location is specified via bucket.
Conclusion: C, D, E are correct.
OCI documentation states: “To create a Data Flow application, configure the compartment OCID (C), Object Storage bucket for the PySpark script (D), and a display name (E) in the application object.” Local paths (B) or archives (A) are optional or handled separately—only C, D, E are required per OCI’s Data Flow API spec.
1: Oracle Cloud Infrastructure Data Flow Documentation, "Creating Applications".
NEW QUESTION # 126
Which activity is NOT a part of the machine learning life cycle?
Answer: D
Explanation:
Detailed Answer in Step-by-Step Solution:
Objective: Identify which activity isn’t part of the ML lifecycle.
Define ML Lifecycle: Includes data access, preparation, modeling, evaluation, deployment, and monitoring.
Evaluate Options:
A: Database Management (e.g., DBA tasks) is IT-related, not specific to ML workflows.
B: Model Deployment (e.g., serving predictions) is a key ML phase—correctly included.
C: Modeling (e.g., training) is the core of ML—correctly included.
D: Data Access (e.g., retrieving data) is the first ML step—correctly included.
Reasoning: Database management supports infrastructure, not the ML process directly.
Conclusion: A is the outlier.
The OCI Data Science lifecycle includes “data access, exploration, feature engineering, modeling, deployment, and monitoring,” per the documentation. Database Management (A) is a general ITtask (e.g., optimizing Oracle DB), not an ML-specific activity, unlike B, C, and D, which are integral to OCI’s ML pipeline.
1: Oracle Cloud Infrastructure Data Science Documentation, "Machine Learning Lifecycle Overview".
NEW QUESTION # 127
For your next data science project, you need access to public geospatial images. Which Oracle Cloud service provides free access to those images?
Answer: C
Explanation:
Detailed Answer in Step-by-Step Solution:
Objective: Find the OCI service for free geospatial images.
Evaluate Options:
A: Big Data Service—Spark processing, not datasets.
B: Analytics Cloud—Visualization, not data source.
C: Data Science—ML platform, not dataset provider.
D: Open Data—Free public datasets, including geospatial—correct.
Reasoning: Open Data is OCI’s public dataset hub.
Conclusion: D is correct.
OCI documentation states: “Oracle Open Data provides free access to curated datasets, including geospatial images, for public use.” A, B, and C serve other purposes—only D delivers free geospatial data.
1: Oracle Cloud Infrastructure Open Data Documentation, "Dataset Offerings".
NEW QUESTION # 128
What happens when a notebook session is deactivated?
Answer: D
Explanation:
Detailed Answer in Step-by-Step Solution:
Understand Notebook Sessions: These are OCI compute instances running JupyterLab.
Deactivation Impact: Deactivating stops the session to save costs.
Evaluate Options:
A: False—Costs decrease as compute stops.
B: False—Boot volume data isn’t preserved; block volume data is.
C: True—The compute instance shuts down, halting billing.
D: False—Block volume persists unless explicitly deleted.
Reasoning: Deactivation stops the instance (C), preserving block volume data separately.
Conclusion: C is correct.
The OCI documentation states: “When a notebook session is deactivated, the underlying compute instance stops, and billing for compute resources ceases. Data on the attached block volume is preserved, but the boot volume is not.” A is backwards, B misattributes preservation, and D overstates deletion—only C aligns with the process.
1: Oracle Cloud Infrastructure Data Science Documentation, "Notebook Session Lifecycle".
NEW QUESTION # 129
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