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| Section | Objectives |
|---|---|
| Use Related OCI Services | - Design machine learning solutions for business use cases - Apply OCI services for data ingestion, storage, and processing - Integrate OCI Data and AI services |
| OCI Data Science - Introduction and Configuration | - Use OCI Data Science notebooks and sessions - Understand OCI Data Science service concepts and architecture - Configure and manage Data Science resources |
| 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 |
| Apply MLOps Practices | - Monitor and maintain machine learning models - Implement model lifecycle management - Use best practices for operationalizing ML solutions |
| 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 |
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NEW QUESTION # 156
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 # 157
In which two ways can you improve data durability in Oracle Cloud Infrastructure Object Storage?
Answer: B,E
Explanation:
Detailed Answer in Step-by-Step Solution:
Objective: Identify two methods to enhance Object Storage durability.
Understand Durability: Ensures data isn’t lost—focus on redundancy and protection.
Evaluate Options:
A: RAID1—Block volume feature, not Object Storage.
B: Encryption—Secures data, not durability.
C: Versioning—Retains old versions, prevents loss—correct.
D: Limit delete—Prevents accidental deletion—correct.
E: Client encryption—Secures, not durability-focused.
Reasoning: C and D directly protect against data loss—durability-focused.
Conclusion: C and D are correct.
OCI documentation states: “Improve Object Storage durability with Versioning (C) to retain previous object versions and by limiting delete permissions (D) to prevent accidental loss.” A isn’t applicable, B and E focus on security—only C and D enhance durability per OCI’s storage features.
1: Oracle Cloud Infrastructure Object Storage Documentation, "Data Durability Options".
NEW QUESTION # 158
Which OCI service enables you to build, train, and deploy machine learning models in the cloud?
Answer: C
Explanation:
Detailed Answer in Step-by-Step Solution:
Objective: Identify the OCI service for ML model lifecycle.
Evaluate Options:
A: Data Catalog—Metadata management, not ML.
B: Data Integration—ETL, not ML.
C: Data Science—Full ML lifecycle—correct.
D: Data Flow—Spark processing, not full ML.
Reasoning: C supports building, training, deploying models.
Conclusion: C is correct.
OCI documentation states: “OCI Data Science (C) provides tools to build, train, and deploy machine learning models in the cloud, including notebooks and model catalog.” A, B, and D serve other purposes—only C fits the ML lifecycle per OCI’s offerings.
1: Oracle Cloud Infrastructure Data Science Documentation, "Service Overview".
NEW QUESTION # 159
What is the name of the machine learning library used in Apache Spark?
Answer: A
Explanation:
Detailed Answer in Step-by-Step Solution:
Objective: Identify Apache Spark’s ML library.
Understand Spark: A big data framework with specialized libraries.
Evaluate Options:
A: MLib (correctly MLlib)—Spark’s machine learning library.
B: GraphX—Graph processing, not ML.
C: Structured Streaming—Streaming data, not ML.
D: HadoopML—Not a Spark library (Hadoop-related).
Reasoning: MLlib is Spark’s official ML toolkit (e.g., regression, clustering).
Conclusion: A is correct (noting “MLib” should be “MLlib”).
OCI Data Science supports Spark via Data Flow, where “MLlib (Machine Learning library) provides scalable ML algorithms.” GraphX (B) and Structured Streaming (C) serve other purposes, and HadoopML (D) isn’t real—MLlib (A) is the standard, despite the typo.
1: Oracle Cloud Infrastructure Data Flow Documentation, "Apache Spark MLlib".
NEW QUESTION # 160
You are a data scientist; you use the Oracle Cloud Infrastructure (OCI) Language service to train custom models. Which types of custom models can be trained?
Answer: D
Explanation:
Detailed Answer in Step-by-Step Solution:
Objective: Identify custom model types for OCI Language.
Understand OCI Language: Focuses on text analysis.
Evaluate Options:
A: Image classification—Not text-based, incorrect.
B: Text classification, NER—Both text tasks—correct.
C: Sentiment, NER—Sentiment is pretrained, not custom.
D: Object detection—Image-based, incorrect.
Reasoning: B aligns with OCI Language’s text custom models.
Conclusion: B is correct.
OCI Language documentation states: “Custom models can be trained for text classification and Named Entity Recognition (NER) using your data.” Image tasks (A, D) are for Vision, and sentiment (C) is pretrained—only B fits OCI Language’s scope.
1: Oracle Cloud Infrastructure Language Documentation, "Custom Model Training".
NEW QUESTION # 161
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