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Oracle 1z0-1110-25 Exam Syllabus Topics:

Topic	Details
Topic 1	Implement End-to-End Machine Learning Lifecycle: This section evaluates the abilities of Machine Learning Engineers and includes an end-to-end walkthrough of the ML lifecycle within OCI. It involves data acquisition from various sources, data preparation, visualization, profiling, model building with open-source libraries, Oracle AutoML, model evaluation, interpretability with global and local explanations, and deployment using the model catalog.
Topic 2	Apply MLOps Practices: This domain targets the skills of Cloud Data Scientists and focuses on applying MLOps within the OCI ecosystem. It covers the architecture of OCI MLOps, managing custom jobs, leveraging autoscaling for deployed models, monitoring, logging, and automating ML workflows using pipelines to ensure scalable and production-ready deployments.
Topic 3	Create and Manage Projects and Notebook Sessions: This part assesses the skills of Cloud Data Scientists and focuses on setting up and managing projects and notebook sessions within OCI Data Science. It also covers managing Conda environments, integrating OCI Vault for credentials, using Git-based repositories for source code control, and organizing your development environment to support streamlined collaboration and reproducibility.
Topic 4	OCI Data Science - Introduction & Configuration: This section of the exam measures the skills of Machine Learning Engineers and covers foundational concepts of Oracle Cloud Infrastructure (OCI) Data Science. It includes an overview of the platform, its architecture, and the capabilities offered by the Accelerated Data Science (ADS) SDK. It also addresses the initial configuration of tenancy and workspace setup to begin data science operations in OCI.
Topic 5	Use Related OCI Services: This final section measures the competence of Machine Learning Engineers in utilizing OCI-integrated services to enhance data science capabilities. It includes creating Spark applications through OCI Data Flow, utilizing the OCI Open Data Service, and integrating other tools to optimize data handling and model execution workflows.

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Oracle Cloud Infrastructure 2025 Data Science Professional Sample Questions (Q128-Q133):

NEW QUESTION # 128
What is the name of the machine learning library used in Apache Spark?

A. Structured Streaming
B. HadoopML
C. GraphX
D. MLib

Answer: D

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

NEW QUESTION # 129
You want to create a user group for a team of external data science consultants. The consultants should only have the ability to see Data Science resource details but not have the ability to create, delete, or update Data Science resources. What verb should you write in the policy?

A. Read
B. Use
C. Inspect
D. Manage

Answer: C

Explanation:
Detailed Answer in Step-by-Step Solution:
* Understand OCI IAM Policies: Policies control access using verbs like "inspect," "read," "use," and
"manage."
* Define Requirement: Consultants need view-only access without modification rights.
* Evaluate Verbs:
* A. Use: Allows interaction (e.g., running jobs)-too permissive.
* B. Inspect: Grants view-only access to resource details-matches requirement.
* C. Manage: Full control (create, update, delete)-too permissive.
* D. Read: Includes viewing content (e.g., data), not just metadata-slightly broader than needed.
* Conclusion: "Inspect" (B) is the precise verb for view-only access to resource details.
In OCI Identity and Access Management (IAM), the "inspect" verb allows listing and viewing resource metadata without granting modification or data access rights, ideal for this scenario. This is confirmed in the IAM policy reference. (Reference: Oracle Cloud Infrastructure Documentation, "IAM Policy Verbs").

NEW QUESTION # 130
You want to write a Python script to create a collection of different projects for your data science team. Which Oracle Cloud Infrastructure (OCI) Data Science interface would you use?

A. The OCI Software Development Kit (SDK)
B. Mobile App
C. OCI Console
D. Command Line Interface (CLI)

Answer: A

Explanation:
Detailed Answer in Step-by-Step Solution:
* Objective: Choose an interface for a Python script to manage projects.
* Evaluate Options:
* A: OCI SDK-Python-based, scriptable-correct.
* B: Console-GUI, not scriptable.
* C: CLI-Command-based, not Python-native.
* D: Mobile App-Not for scripting.
* Reasoning: A enables programmatic project creation.
* Conclusion: A is correct.
OCI documentation states: "Use the OCI Python SDK (A) to programmatically manage Data Science resources, like creating projects, via Python scripts." B, C, and D don't support Python scripting-only A fits.
Oracle Cloud Infrastructure SDK Documentation, "Data Science API".

NEW QUESTION # 131
Which OCI service provides a managed Kubernetes service for deploying, scaling, and managing containerized applications?

A. Oracle Cloud Infrastructure Load Balancing
B. Oracle Cloud Infrastructure Container Engine for Kubernetes
C. Oracle Cloud Infrastructure Container Registry
D. Oracle Cloud Infrastructure Streaming

Answer: B

Explanation:
Detailed Answer in Step-by-Step Solution:
* Objective: Identify OCI's managed Kubernetes service.
* Evaluate Options:
* A: Container Registry-Stores images, not Kubernetes.
* B: Load Balancing-Network service, not Kubernetes.
* C: Container Engine (OKE)-Managed Kubernetes-correct.
* D: Streaming-Data streaming, not containers.
* Reasoning: C is OCI's Kubernetes offering-OKE.
* Conclusion: C is correct.
OCI documentation states: "OCI Container Engine for Kubernetes (OKE) (C) provides a managed service to deploy, scale, and manage containerized applications using Kubernetes." A, B, and D serve other purposes- only C matches per OCI's container services.
Oracle Cloud Infrastructure OKE Documentation, "Overview".

NEW QUESTION # 132
You are working in your notebook session and find that your notebook session does not have enough compute CPU and memory for your workload. How would you scale up your notebook session without losing your work?

A. Deactivate your notebook session, provision a new notebook session on a larger compute shape, and recreate all your file changes
B. Download your files and data to your local machine, delete your notebook session, provision a new notebook session on a larger compute shape, and upload your files from your local machine to the new notebook session
C. Ensure your files and environments are written to the block volume storage under the /home
/datascience directory, deactivate the notebook session, and activate the notebook with a larger compute shape selected
D. Create a temporary bucket in Object Storage, write all your files and data to Object Storage, delete the notebook session, provision a new notebook session on a larger compute shape, and copy your files and data from your temporary bucket to your new notebook session

Answer: C

Explanation:
Detailed Answer in Step-by-Step Solution:
* Objective: Scale up a notebook session without losing work.
* Understand Persistence: Block volume stores session data (e.g., /home/datascience).
* Evaluate Options:
* A: Recreating work-inefficient, risks loss.
* B: Local download/upload-cumbersome, unnecessary.
* C: Use block volume persistence, scale up-efficient, preserves work-correct.
* D: Object Storage-extra steps, not needed with block volume.
* Reasoning: C leverages OCI's built-in persistence for seamless scaling.
* Conclusion: C is correct.
OCI documentation states: "Files in /home/datascience are stored on the block volume. To scale up, deactivate the session, provision a new one with a larger shape, and the block volume persists your work." A loses data, B and D add complexity-only C is optimal.
Oracle Cloud Infrastructure Data Science Documentation, "Scaling Notebook Sessions".

NEW QUESTION # 133
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