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Oracle 1z0-1110-25 시험요강:

주제	소개
주제 1	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.
주제 2	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.
주제 3	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.
주제 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.
주제 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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퍼펙트한Oracle 1z0-1110-25시험대비덤프자료는 Itexamdump가 전문입니다. Oracle 1z0-1110-25덤프를 다운받아 가장 쉬운 시험준비를 하여 한방에 패스가는것입니다. 다같이 Oracle 1z0-1110-25덤프로 시험패스에 주문걸어 보아요. 마술처럼Oracle 1z0-1110-25시험합격이 실현될것입니다.

최신 Oracle Cloud 1z0-1110-25 무료샘플문제 (Q68-Q73):

질문 # 68
Triggering a PagerDuty notification as part of Monitoring is an example of what in the OCI Console?

A. Function
B. Event
C. Action
D. Rule

정답：C

설명：
Detailed Answer in Step-by-Step Solution:
* Objective: Classify a PagerDuty notification in OCI Monitoring.
* Understand OCI Monitoring: Involves events, rules, and actions for notifications.
* Evaluate Options:
* A: Action-executes a response (e.g., notify PagerDuty) when triggered-correct.
* B: Rule-defines conditions for triggering actions-precedes the action.
* C: Function-serverless code, not directly tied to notifications.
* D: Event-state change triggering a rule, not the notification itself.
* Reasoning: The notification is the action taken after an event/rule-fits A.
* Conclusion: A is correct.
OCI documentation states: "Actions in the Monitoring service execute responses, such as sending notifications to PagerDuty, when a rule's condition is met based on an event." Rules (B) set conditions, Functions (C) are unrelated, and Events (D) are triggers-only Action (A) describes the notification step.
Oracle Cloud Infrastructure Monitoring Documentation, "Actions Overview".

질문 # 69
You are a data scientist designing an air traffic control model, and you choose to leverage Oracle AutoML.
You understand that the Oracle AutoML pipeline consists of multiple stages and automatically operates in a certain sequence. What is the correct sequence for the Oracle AutoML pipeline?

A. Algorithm selection, Adaptive sampling, Feature selection, Hyperparameter tuning
B. Algorithm selection, Feature selection, Adaptive sampling, Hyperparameter tuning
C. Adaptive sampling, Feature selection, Algorithm selection, Hyperparameter tuning
D. Adaptive sampling, Algorithm selection, Feature selection, Hyperparameter tuning

정답：C

설명：
Detailed Answer in Step-by-Step Solution:
* Objective: Sequence OCI AutoML pipeline stages.
* Stages:
* Adaptive sampling: Reduces data size if large.
* Feature selection: Picks relevant features.
* Algorithm selection: Chooses best model type.
* Hyperparameter tuning: Optimizes model params.
* Evaluate: C (sampling, features, algorithms, tuning) matches logical flow-data first, then model.
* Reasoning: Sampling precedes feature work-standard in OCI.
* Conclusion: C is correct.
OCI documentation states: "AutoML pipeline runs 1) adaptive sampling, 2) feature selection, 3) algorithm selection, 4) hyperparameter tuning (C)." Sampling reduces data first, then features and models are optimized-other orders (A, B, D) misalign with OCI's sequence.
Oracle Cloud Infrastructure AutoML Documentation, "Pipeline Sequence".

질문 # 70
Which OCI Data Science interaction method can function without the need of scripting?

A. CLI
B. REST APIs
C. OCI Console
D. Language SDKs

정답：C

설명：
Detailed Answer in Step-by-Step Solution:
* Objective: Identify the OCI Data Science interaction method that doesn't require scripting.
* Understand Interaction Methods: OCI provides multiple ways to interact with Data Science services- some are GUI-based, others script-based.
* Evaluate Options:
* A. OCI Console: A web-based graphical interface allowing users to manage resources (e.g., create notebook sessions, deploy models) via point-and-click-no scripting needed.
* B. CLI: Command Line Interface requires writing commands (scripts) to execute tasks (e.g., oci data-science notebook-session create).
* C. Language SDKs: Software Development Kits (e.g., Python SDK) require coding to interact programmatically (e.g., oci.data_science.DataScienceClient).
* D. REST APIs: Application Programming Interfaces require scripted HTTP requests (e.g., using curl or a programming language).
* Reasoning: Only the OCI Console (A) offers a no-code, user-friendly interface, while B, C, and D rely on scripting or programming.
* Conclusion: A is the correct answer as it eliminates the need for scripting.
The OCI Console is described in the documentation as "a browser-based interface that allows users to manage OCI Data Science resources, such as creating notebook sessions or jobs, without writing code or scripts." In contrast, the CLI (B) requires command-line scripts, SDKs (C) need programming (e.g., Python), and REST APIs (D) involve scripted API calls. The Console's GUI distinguishes it as the only option functioning without scripting, aligning with Oracle's design for accessibility to non-programmers.
Oracle Cloud Infrastructure Data Science Documentation, "Getting Started with OCI Console" section.

질문 # 71
Which OCI service enables you to build, train, and deploy machine learning models in the cloud?

A. Oracle Cloud Infrastructure Data Integration
B. Oracle Cloud Infrastructure Data Flow
C. Oracle Cloud Infrastructure Data Science
D. Oracle Cloud Infrastructure Data Catalog

정답：C

설명：
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.
Oracle Cloud Infrastructure Data Science Documentation, "Service Overview".

질문 # 72
You are a data scientist building a pipeline in the Oracle Cloud Infrastructure (OCI) Data Science service for your machine learning project. You want to optimize the pipeline completion time by running some steps in parallel. Which statement is true about running pipeline steps in parallel?

A. Pipeline steps can be run in sequence or in parallel, as long as they create a directed acyclic graph (DAG)
B. All pipeline steps are always run in parallel
C. Steps in a pipeline can be run only sequentially
D. Parallel steps cannot be run if they are completely independent of each other

정답：A

설명：
Detailed Answer in Step-by-Step Solution:
* Objective: Understand parallel execution in OCI Pipelines.
* Evaluate Options:
* A: False-Pipelines support parallelism.
* B: True-DAG allows sequential/parallel steps-correct.
* C: False-Not all steps must be parallel.
* D: False-Independence enables parallelism.
* Reasoning: B reflects OCI's DAG-based flexibility.
* Conclusion: B is correct.
OCI documentation states: "Pipeline steps can run sequentially or in parallel, defined by a directedacyclic graph (DAG) (B), allowing optimization of completion time." A, C, and D misrepresent this-only B aligns with OCI's pipeline design.
Oracle Cloud Infrastructure Data Science Documentation, "Pipeline Parallelism".

질문 # 73
......

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