Detailed Answer in Step-by-Step Solution:
* Objective: Identify a true statement about OCI Data Science Jobs.
* Understand OCI Jobs: Jobs automate ML tasks (e.g., training) on managed infrastructure.
* Evaluate Options:
* A: True-Jobs provision OCI compute resources on-demand for task execution.
* B: False-Users define custom tasks (e.g., Python scripts), not limited to standard ones.
* C: False-Infrastructure is fully managed by OCI, not user-managed.
* D: False-Multiple artifacts (e.g., ZIP with dependencies) can be used, not just one file.
* Reasoning: A reflects OCI's managed, on-demand provisioning model for Jobs.
* Conclusion: A is correct.
The OCI Data Science documentation states: "Jobs provision compute infrastructure on-demand to execute user-defined tasks, such as model training or data processing, on fully managed OCI resources." B is incorrect (customization is allowed), C contradicts the managed nature, and D misstates artifact flexibility-only A accurately describes Jobs.
Oracle Cloud Infrastructure Data Science Documentation, "Jobs Overview".

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.
Oracle Cloud Infrastructure Data Flow Documentation, "Apache Spark MLlib".

Detailed Answer in Step-by-Step Solution:
* Objective: Identify the file system type for OCI File Storage.
* Understand File Storage: Network-attached storage in OCI.
* Evaluate Options:
* A: NFSv3-Network File System, used by File Storage-correct.
* B: iSCSI-Block storage protocol, not File Storage.
* C: Paravirtualized-Virtualization mode, not file system.
* D: NVMe SSD-Hardware, not file system.
* Reasoning: NFSv3 is OCI File Storage's protocol.
* Conclusion: A is correct.
OCI documentation states: "File Storage uses NFSv3 (A) as its file system protocol, providing shared storage across instances." B, C, and D are unrelated-only A aligns with OCI's File Storage design.
Oracle Cloud Infrastructure File Storage Documentation, "File System Protocol".

Detailed Answer in Step-by-Step Solution:
* Objective: Identify an invalid notebook session practice.
* Evaluate Options:
* A: Valid-Long runs should use Jobs, not notebooks.
* B: Valid-Terminal runs with logging are supported.
* C: Valid-Multi-user conflicts are a concern.
* D: Invalid-Copying from Object Storage to block volume is unnecessary; direct access is best.
* E: Valid-Resource principals are secure and recommended.
* Reasoning: D contradicts OCI's direct-access efficiency.
* Conclusion: D is incorrect.
OCI documentation advises: "Access data in Object Storage directly from notebook sessions using SDKs or resource principals-avoid local copies (D) unless necessary." A, B, C, and E are best practices-D is inefficient and not standard.
Oracle Cloud Infrastructure Data Science Documentation, "Notebook Session Best Practices".

Detailed Answer in Step-by-Step Solution:
* Objective: Apply all recommended transformations from get_recommendations() in ADS.
* Understand ADS Tools: get_recommendations() suggests fixes (e.g., missing values).
* Evaluate Options:
* A: Returns transformed data-Not for applying-incorrect.
* B: Sklearn-style, not ADS-specific-incorrect.
* C: auto_transform()-Applies all recommendations-correct.
* D: Visualizes, doesn't apply-incorrect.
* Reasoning: auto_transform() executes the fixes suggested by get_recommendations().
* Conclusion: C is correct.
OCI documentation states: "After get_recommendations() identifies issues, use auto_transform() (C) on the ADSDataset to apply all recommended transformations at once." A retrieves, B is external, D visualizes- only C aligns with OCI's ADS transformation workflow.
Oracle Cloud Infrastructure ADS SDK Documentation, "Data Transformation Methods".