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| Section | Objectives |
|---|---|
| OCI Data Science - Introduction and Configuration | - Configure and manage Data Science resources - Use OCI Data Science notebooks and sessions - Understand OCI Data Science service concepts and architecture |
| Use Related OCI Services | - Integrate OCI Data and AI services - Apply OCI services for data ingestion, storage, and processing - Design machine learning solutions for business use cases |
| Implement End-to-End Machine Learning Lifecycle | - Save and manage models using Model Catalog - Automate machine learning workflows and pipelines - Build, train, and evaluate machine learning models - Deploy models and consume model endpoints - Prepare and manage datasets |
| Apply MLOps Practices | - Implement model lifecycle management - Monitor and maintain machine learning models - Use best practices for operationalizing ML solutions |
| Design and Set Up Data Science Workspace | - Create and configure Data Science projects - Use Accelerated Data Science SDK and open source tools - Manage notebook sessions and compute resources |
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NEW QUESTION # 63
You are attempting to save a model from a notebook session to the model catalog by using the Accelerated Data Science (ADS) SDK, with resource principal as the authentication signer, and you get a 404 authentication error. Which two should you look for to ensure permissions are set up correctly?
Answer: B,E
Explanation:
Detailed Answer in Step-by-Step Solution:
Objective: Troubleshoot a 404 auth error when saving a model with resource principal.
Understand Resource Principal: Allows notebook sessions to act as principals via dynamic groups and policies—no user credentials.
Analyze 404 Error: Indicates permission failure—likely IAM misconfiguration.
Evaluate Options:
A: Block volume storage—Irrelevant to auth; it’s about saving locally—incorrect.
B: Dynamic group matching—Ensures notebook is recognized—correct.
C: User group policy—Not used with resource principal—incorrect.
D: Dynamic group policy—Grants catalog access—correct.
E: Service Gateway—Network-related, not auth-specific—incorrect.
Reasoning: Resource principal needs B (group inclusion) and D (policy perms)—404 points to these.
Conclusion: B and D are correct.
OCI documentation states: “For ADS SDK to save to the Model Catalog using resource principal, ensure (1) a dynamic group includes notebook sessions with matching rules (e.g., resource.type ='datasciencenotebooksession') (B), and (2) a policy grants manage data-science-models to that dynamic group (D).” A is storage, C is user-based, E is network—only B and D fix the auth issue per OCI’s IAM setup.
1: Oracle Cloud Infrastructure Data Science Documentation, "Resource Principal with Model Catalog".
NEW QUESTION # 64
Which statement about resource principals is true?
Answer: D
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 # 65
Which of the following programming languages are most widely used by data scientists?
Answer: C
Explanation:
Detailed Answer in Step-by-Step Solution:
Objective: Identify top languages for data science.
Evaluate Options:
A: C/C++—Low-level, less common for data tasks.
B: Python (ML, libraries), R (stats), SQL (data)—Industry standards.
C: Java (enterprise), JavaScript (web)—Not data-focused.
Reasoning: B aligns with data science tools (e.g., pandas, ggplot).
Conclusion: B is correct.
OCI documentation highlights “Python, R, and SQL as the most widely used languages in Data Science for modeling, analysis, and data querying.” C/C++ (A) and Java/JS (C) are less prevalent—B matches OCI’s notebook support and industry trends.
1: Oracle Cloud Infrastructure Data Science Documentation, "Supported Languages".
NEW QUESTION # 66
You are a computer vision engineer building an image recognition model. You decide to use Oracle Data Labeling to annotate your image dat a. Which of the following THREE are possible ways to annotate an image in Data Labeling?
Answer: A,D,E
Explanation:
Detailed Answer in Step-by-Step Solution:
Objective: Identify three annotation methods in OCI Data Labeling for images.
Understand Data Labeling: Supports image annotations for ML.
Evaluate Options:
A: Semantic segmentation with boxes—Incorrect; segmentation is pixel-based, not boxes.
B: Single label (classification)—Supported—correct.
C: No bounding boxes—False; boxes are supported.
D: Object detection with boxes—Supported—correct.
E: Multiple labels (multi-label)—Supported—correct.
Reasoning: B (classification), D (detection), E (multi-label) match OCI capabilities.
Conclusion: B, D, E are correct.
OCI documentation states: “Data Labeling supports image annotations via single-label classification (B), object detection with bounding boxes (D), and multi-label classification (E).” A misdefines segmentation, C contradicts support—only B, D, E are valid per OCI’s Data Labeling features.
1: Oracle Cloud Infrastructure Data Labeling Documentation, "Image Annotation Types".
NEW QUESTION # 67
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?
Answer: B
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.
1: Oracle Cloud Infrastructure Vision Documentation, "Document Analysis Features".
NEW QUESTION # 68
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