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| Section | Weight | Objectives |
|---|---|---|
| Integrate Related OCI Services | 10% | - Use OCI AI and data services with Data Science - Integration with OCI Object Storage, Vault, and Networking |
| Implement End-to-End Machine Learning Lifecycle | 45% | - Deploy models and manage endpoints - Data preparation, exploration, and transformation - Model saving, cataloging, and versioning - Model development, training, and evaluation - Use AutoML and built-in algorithms |
| Apply MLOps Practices | 20% | - Model monitoring, drift detection, and performance tracking - ML pipelines, automation, and reproducibility - Governance, auditing, and compliance |
| Design and Set Up Data Science Workspace | 15% | - Manage access control, security, and IAM integration - Create and manage projects and notebook sessions - Configure compute shapes, storage, and networking |
| OCI Data Science - Introduction & Configuration | 10% | - Overview and core concepts of OCI Data Science - Capabilities of the Accelerated Data Science (ADS) SDK - Tenancy and environment configuration for Data Science |
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NEW QUESTION # 61
You are a data scientist working for a utilities company. You have developed an algorithm that detects anomalies from a utility reader in the grid. The size of the model artifact is about 2 GB, and you are trying to store it in the model catalog. Which THREE interfaces could you use to save the model artifact into the model catalog?
Answer: B,C,D
Explanation:
Detailed Answer in Step-by-Step Solution:
Objective: Identify interfaces to save a 2 GB model to the Model Catalog.
Evaluate Options:
A: OCI CLI—Supports Data Science tasks—possible but not primary.
B: ADS SDK—Designed for model catalog ops—correct.
C: ODSC CLI—Not standard; likely typo for OCI CLI.
D: Console—GUI for catalog uploads—correct.
E: OCI Python SDK—Programmatic catalog access—correct.
F: Git CLI—Version control, not catalog-related.
Reasoning: B, D, E are OCI’s primary interfaces; A is valid but less emphasized.
Conclusion: B, D, E are correct (A plausible but not top-tier).
OCI documentation lists “ADS SDK (B), OCI Console (D), and OCI Python SDK (E) as primary methods to save models to the Model Catalog.” OCI CLI (A) works but isn’t highlighted, C isn’t real, and F is unrelated—B, D, E are the standard trio.
1: Oracle Cloud Infrastructure Data Science Documentation, "Model Catalog Interfaces".
NEW QUESTION # 62
You are a data scientist using Oracle AutoML to produce a model and you are evaluating the score metric for the model. Which TWO of the following prevailing metrics would you use for evaluating a multiclass classification model?
Answer: A,C
Explanation:
Detailed Answer in Step-by-Step Solution:
Understand Multiclass Classification: Metrics evaluate how well the model predicts multiple classes.
Evaluate Metrics:
A . Mean squared error: Used for regression, not classification.
B . Explained variance score: Regression metric, not suitable.
C . Recall: Measures true positive rate per class—key for classification.
D . F1-score: Balances precision and recall—widely used in multiclass.
E . R-squared: Regression metric, not applicable.
Select Two: Recall (C) and F1-score (D) are standard for multiclass classification.
Oracle AutoML supports metrics like recall and F1-score for multiclass classification, as they assess per-class performance and overall precision-recall balance, respectively. Regression metrics (A, B,E) are irrelevant here. (Oracle Cloud Infrastructure Data Science Documentation, "AutoML Metrics").
NEW QUESTION # 63
Which TWO statements about Oracle Cloud Infrastructure (OCI) Open Data service are true?
Answer: B,D
Explanation:
Detailed Answer in Step-by-Step Solution:
Analyze OCI Open Data: OCI Open Data is a free service providing access to public datasets for AI/ML use cases.
Evaluate Statements:
A: True—Open Data includes text and image datasets (e.g., geospatial images).
B: False—Video and other formats may be available depending on the dataset; no strict exclusion exists.
C: False—Datasets may include metadata, but code/tooling examples aren’t guaranteed.
D: True—It’s designed for data scientists and analysts who work with datasets.
E: False—It’s not a user-contributed repository; it’s curated by Oracle.
F: False—Open Data is free and public, not subscription-based.
Select Two: A and D align with the service’s purpose and offerings.
OCI Open Data provides access to datasets like text and images (A) for AI/ML, aimed at data professionals (D). It’s a free, curated service, not user-contributed (E) or paid (F), and while it focuses on certain formats, it doesn’t explicitly exclude audio/video (B). (Oracle Cloud Infrastructure Open Data Documentation, "Overview of Open Data").
NEW QUESTION # 64
Which feature of Oracle Cloud Infrastructure Data Science provides an interactive coding environment for building and training machine learning models?
Answer: D
Explanation:
Detailed Answer in Step-by-Step Solution:
Objective: Identify the interactive coding environment in OCI Data Science.
Evaluate Options:
A: Model Catalog stores models—not for coding.
B: Jobs run predefined tasks—not interactive.
C: Notebook Sessions provide JupyterLab for coding and training—interactive.
D: Projects organize work—not a coding environment.
Reasoning: Notebook Sessions are OCI’s Jupyter-based tool for interactive ML development.
Conclusion: C is correct.
OCI Data Science Notebook Sessions “provide an interactive JupyterLab environment where data scientists can write code, explore data, and train machine learning models.” Model Catalog (A) is for storage, Jobs (B) for automation, and Projects (D) for organization—only C offers interactivity.
1: Oracle Cloud Infrastructure Data Science Documentation, "Notebook Sessions Overview".
NEW QUESTION # 65
What happens when a notebook session is deactivated?
Answer: C
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 # 66
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