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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: OCI Data Science - Introduction and Configuration | - Use OCI Data Science notebooks and sessions - Configure and manage Data Science resources - Understand OCI Data Science service concepts and architecture |
| Topic 3: Design and Set Up Data Science Workspace | - Use Accelerated Data Science SDK and open source tools - Create and configure Data Science projects - Manage notebook sessions and compute resources |
| Topic 4: Implement End-to-End Machine Learning Lifecycle | - Deploy models and consume model endpoints - Automate machine learning workflows and pipelines - Build, train, and evaluate machine learning models - Save and manage models using Model Catalog - Prepare and manage datasets |
| Topic 5: 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 |
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NEW QUESTION # 61
You are a data scientist working inside a notebook session and you attempt to pip install a package from a public repository that is not included in your conda environment. After running this command, you get a network timeout error. What might be missing from your networking configuration?
Answer: B
Explanation:
Detailed Answer in Step-by-Step Solution:
Objective: Fix network timeout for pip install in a notebook.
Evaluate Options:
A: FastConnect—On-premises link, not public internet.
B: VNIC—Default, not the issue.
C: NAT Gateway—Grants internet access—correct.
D: Service Gateway—OCI services, not PyPI.
Reasoning: C enables outbound traffic to public repos.
Conclusion: C is correct.
OCI documentation states: “A NAT Gateway (C) is required for notebook sessions in private subnets to access public internet repositories like PyPI.” A, B, and D don’t provide this—only C resolves the timeout.
1: Oracle Cloud Infrastructure Data Science Documentation, "Notebook Networking".
NEW QUESTION # 62
Which Oracle Cloud Service provides restricted access to target resources?
Answer: C
Explanation:
Detailed Answer in Step-by-Step Solution:
Objective: Identify the OCI service for restricted resource access.
Evaluate Options:
A: Bastion—Secure, temporary access to resources—correct.
B: Internet Gateway—Public access, not restricted.
C: Load Balancer—Distributes traffic, not access control.
D: SSL Certificate—Secures comms, not access.
Reasoning: Bastion limits access (e.g., SSH) to specific targets.
Conclusion: A is correct.
OCI documentation states: “OCI Bastion (A) provides restricted, audited access to target resources like instances, typically via SSH.” B, C, and D don’t restrict—only A fits per OCI’s security services.
1: Oracle Cloud Infrastructure Bastion Documentation, "Overview".
NEW QUESTION # 63
As a data scientist, you require a pipeline to train ML models. When can a pipeline run be initiated?
Answer: D
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 # 64
You are a data scientist with a set of text and image files that need annotation, and you want to use Oracle Cloud Infrastructure (OCI) Data Labeling. Which of the following THREE annotation classes are supported by the tool?
Answer: A,E,F
Explanation:
Detailed Answer in Step-by-Step Solution:
Objective: Identify supported annotation classes in OCI Data Labeling.
Understand Tool: Supports image/text annotations for ML.
Evaluate Options:
A: Object detection—Yes (bounding boxes).
B: Named entity—Text-specific, not primary for images.
C: Classification—Yes (labels for images/text).
D: Key-point—Not listed in OCI docs.
E: Polygonal—Not explicitly supported.
F: Semantic segmentation—Yes (pixel-level).
Reasoning: A, C, F match OCI’s image/text focus.
Conclusion: A, C, F are correct.
OCI Data Labeling supports “object detection (A), classification (C), and semantic segmentation (F) for images and text,” per documentation. B is text-specific, D and E aren’t highlighted—only A, C, F are core classes.
1: Oracle Cloud Infrastructure Data Labeling Documentation, "Annotation Types".
NEW QUESTION # 65
Which encryption is used for Oracle Data Science?
Answer: C
Explanation:
Detailed Answer in Step-by-Step Solution:
Objective: Identify encryption standard for OCI Data Science.
Understand OCI Encryption: Applies to data at rest and in transit.
Evaluate Options:
A: AES-256—Industry-standard, OCI default—correct.
B: DES—Outdated, weak—incorrect.
C: TDES—Older, less secure—incorrect.
D: Twofish—Not OCI standard—incorrect.
E: RSA—Asymmetric, not primary for data at rest—incorrect.
Reasoning: AES-256 is OCI’s go-to for Data Science resources.
Conclusion: A is correct.
OCI documentation states: “Data Science services encrypt data at rest using AES-256 (A), ensuring high security for notebooks, jobs, and models.” B, C, D, and E are either outdated or not used—only A matches OCI’s encryption policy.
1: Oracle Cloud Infrastructure Data Science Documentation, "Data Encryption".
NEW QUESTION # 66
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