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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Implement End-to-End Machine Learning Lifecycle | 45% | - Deploy models and manage endpoints - Use AutoML and built-in algorithms - Data preparation, exploration, and transformation - Model development, training, and evaluation - Model saving, cataloging, and versioning |
| Topic 2: Design and Set Up Data Science Workspace | 15% | - Configure compute shapes, storage, and networking - Create and manage projects and notebook sessions - Manage access control, security, and IAM integration |
| Topic 3: Integrate Related OCI Services | 10% | - Use OCI AI and data services with Data Science - Integration with OCI Object Storage, Vault, and Networking |
| Topic 4: 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 |
| Topic 5: Apply MLOps Practices | 20% | - Model monitoring, drift detection, and performance tracking - ML pipelines, automation, and reproducibility - Governance, auditing, and compliance |
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NEW QUESTION # 47
Select two reasons why it is important to rotate encryption keys when using Oracle Cloud Infrastructure (OCI) Vault to store credentials or other secrets.
Answer: A,E
Explanation:
Detailed Answer in Step-by-Step Solution:
Objective: Identify two reasons for key rotation in OCI Vault.
Understand Key Rotation: Enhances security by updating keys.
Evaluate Options:
A: Five-key limit—False, no such restriction.
B: Efficiency—False, not the purpose.
C: Reuse—False, rotation prevents reuse.
D: Reduces risk—True, limits exposure—correct.
E: Limits data—True, reduces breach scope—correct.
Reasoning: D and E are security-focused—key Vault benefits.
Conclusion: D and E are correct.
OCI documentation states: “Key rotation in Vault (D) reduces risk if a key is compromised and (E) limits the data encrypted by a single key version, enhancing security.” A, B, and C misrepresent rotation’s purpose—only D and E align with OCI’s Vault best practices.
1: Oracle Cloud Infrastructure Vault Documentation, "Key Rotation Benefits".
NEW QUESTION # 48
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,D
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 # 49
The Oracle AutoML pipeline automates hyperparameter tuning by training the model with different parameters in parallel. You have created an instance of Oracle AutoML as oracle_automl and now you want an output with all the different trials performed by Oracle AutoML. Which of the following commands gives you the results of all trials?
Answer: D
Explanation:
Detailed Answer in Step-by-Step Solution:
Objective: Get all AutoML trial results.
Understand AutoML: Trials include hyperparameter tuning outcomes.
Evaluate Options:
A: print_trials()—Displays all trial results—correct.
B: visualize_tuning_trials()—Visualizes tuning, not full list.
C: visualize_adaptive_sampling_trials()—Specific to sampling, not all trials.
D: visualize_algorithm_selection_trials()—Specific to algorithms, not all.
Reasoning: A provides comprehensive trial output.
Conclusion: A is correct.
OCI AutoML documentation states: “print_trials() outputs a table of all trials performed, including hyperparameters and scores.” Visualization methods (B, C, D) focus on specific aspects—only A gives the full list.
1: Oracle Cloud Infrastructure AutoML Documentation, "Trial Output Methods".
NEW QUESTION # 50
Which statement about Oracle Cloud Infrastructure Multi-Factor Authentication (MFA) is NOT valid?
Answer: B
Explanation:
Detailed Answer in Step-by-Step Solution:
Objective: Identify the invalid MFA statement.
Evaluate Options:
A: True—Users can’t disable MFA; admin-controlled.
B: False—Multiple devices can be registered—invalid.
C: True—Authenticator app is required.
D: True—Admins can disable MFA.
Reasoning: B contradicts OCI’s multi-device support.
Conclusion: B is incorrect.
OCI documentation states: “Users can register multiple devices for MFA (B is false), must use an authenticator app (C), and cannot disable MFA themselves (A)—admins can (D).” Only B is not valid per OCI’s IAM MFA policy.
1: Oracle Cloud Infrastructure IAM Documentation, "Multi-Factor Authentication".
NEW QUESTION # 51
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 # 52
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