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| Section | Weight | Objectives |
|---|---|---|
| Apply MLOps Practices | 20% | - Governance, auditing, and compliance - Model monitoring, drift detection, and performance tracking - ML pipelines, automation, and reproducibility |
| Integrate Related OCI Services | 10% | - Integration with OCI Object Storage, Vault, and Networking - Use OCI AI and data services with Data Science |
| Implement End-to-End Machine Learning Lifecycle | 45% | - Model saving, cataloging, and versioning - Model development, training, and evaluation - Data preparation, exploration, and transformation - Deploy models and manage endpoints - Use AutoML and built-in algorithms |
| Design and Set Up Data Science Workspace | 15% | - Create and manage projects and notebook sessions - Manage access control, security, and IAM integration - Configure compute shapes, storage, and networking |
| OCI Data Science - Introduction & Configuration | 10% | - Capabilities of the Accelerated Data Science (ADS) SDK - Overview and core concepts of OCI Data Science - Tenancy and environment configuration for Data Science |
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NEW QUESTION # 123
Which statement is true about standards?
Answer: A
Explanation:
Detailed Answer in Step-by-Step Solution:
Objective: Identify a true statement about standards in an OCI context (likely governance/security).
Understand Standards: Rules or benchmarks, often compliance-related.
Evaluate Options:
A: Auditable—True; standards are checked for adherence.
B: Result of requirements—Partially true, but not always.
C: Methods/instructions—More procedural, not defining standards.
D: Foundation of governance—Broad, not specific to standards.
Reasoning: A is universally true—standards face audits (e.g., SOC, ISO).
Conclusion: A is correct.
OCI documentation notes: “Standards (e.g., security standards) may be audited (A) to ensure compliance with OCI policies or external regulations.” B is a source, C describes procedures, D is too vague—only A is consistently true per OCI’s compliance framework.
1: Oracle Cloud Infrastructure Security Documentation, "Compliance and Standards".
NEW QUESTION # 124
Which CLI command allows the customized conda environment to be shared with co-workers?
Answer: B
Explanation:
Detailed Answer in Step-by-Step Solution:
Objective: Share a custom conda environment in OCI Data Science.
Understand Commands: OCI provides odsc CLI for environment management.
Evaluate Options:
A: clone duplicates an environment locally—not for sharing.
B: publish uploads the environment to Object Storage for team access—correct.
C: modify doesn’t exist as a standard command.
D: install sets up an environment locally—not for sharing.
Reasoning: Sharing requires publishing to a shared location (Object Storage), which publish achieves.
Conclusion: B is the correct command.
The OCI Data Science CLI documentation states: “Use odsc conda publish to package and upload a custom conda environment to an Object Storage Bucket, making it accessible to other users.” clone (A) is for local duplication, modify (C) isn’t valid, and install (D) is for local setup—not sharing. B is the designated sharing mechanism.
1: Oracle Cloud Infrastructure Data Science CLI Reference, "odsc conda publish".
NEW QUESTION # 125
You are working as a data scientist for a healthcare company. They decided 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 steps to develop a PySpark application in OCI Data Science?
Answer: D
Explanation:
Detailed Answer in Step-by-Step Solution:
Objective: Sequence steps for a PySpark app in OCI Data Science.
Evaluate Steps:
Launch notebook: First—provides the environment.
Install PySpark conda: Second—sets up Spark libraries.
Configure core-site.xml: Third—connects to data (e.g., Object Storage).
Develop app: Fourth—writes the PySpark code.
Data Flow: Fifth—optional scaling, post-development.
Check Options: D (1, 2, 3, 4, 5) matches this logical flow.
Reasoning: Notebook first, then setup, coding, and scaling.
Conclusion: D is correct.
OCI documentation recommends: “1) Launch a notebook session, 2) install a PySpark conda environment, 3) configure core-site.xml for data access, 4) develop your PySpark application, and 5) optionally use Data Flow for scale.” D follows this—others (A, B, C) misorder critical steps like launching the notebook.
1: Oracle Cloud Infrastructure Data Science Documentation, "PySpark in Notebooks".
NEW QUESTION # 126
You are given a task of writing a program that sorts document images by language. Which Oracle AI Service would you use?
Answer: A
Explanation:
Detailed Answer in Step-by-Step Solution:
Objective: Select an OCI AI service to sort images by language.
Evaluate Options:
A: Digital Assistant—Chatbots, not image/language processing.
B: Vision—Image analysis (e.g., object detection), not language sorting.
C: Speech—Audio-to-text, not image-based.
D: Language—Text analysis (e.g., language detection) after OCR—correct.
Reasoning: Images need OCR (Vision) then language detection (Language)—D fits the sorting task.
Conclusion: D is correct.
OCI Language “detects and classifies languages in text,” often paired with OCI Vision’s OCR to process document images. Vision (B) extracts text, but Language (D) sorts by language—Digital Assistant (A) and Speech (C) don’t apply. Documentation supports this workflow.
1: Oracle Cloud Infrastructure Language Documentation, "Language Detection".
NEW QUESTION # 127
As a data scientist, you require a pipeline to train ML models. When can a pipeline run be initiated?
Answer: C
Explanation:
Detailed Answer in Step-by-Step Solution:
Objective: Determine when an OCI Data Science pipeline can start.
Understand Pipelines: They’re workflows with defined steps, executed on demand or scheduled.
Evaluate Options:
A: Once created, a pipeline can be run immediately—correct.
B: “During run state” implies it’s already running—illogical.
C: “After active state” is unclear; pipelines run when triggered, not post-state.
D: “Before active state” is vague—creation precedes running.
Reasoning: Pipelines are executable post-creation via UI/CLI—simplest interpretation is A.
Conclusion: A is correct.
OCI Data Science documentation states: “After a pipeline is created, you can initiate a pipeline run immediately or schedule it using the OCI Console, CLI, or SDK.” B, C, and D misalign with this—running starts post-creation (A), not during/after ambiguous states.
1: Oracle Cloud Infrastructure Data Science Documentation, "Pipelines - Running a Pipeline".
NEW QUESTION # 128
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