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[General] Fast Download Free 1z0-1110-25 Practice Exams - How to Download for Oracle 1z0-1

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【General】 Fast Download Free 1z0-1110-25 Practice Exams - How to Download for Oracle 1z0-1

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Oracle 1z0-1110-25 Exam Syllabus Topics:
TopicDetails
Topic 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.
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
  • 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.
Topic 4
  • 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 5
  • 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.

Oracle Cloud Infrastructure 2025 Data Science Professional Sample Questions (Q31-Q36):NEW QUESTION # 31
Which CLI command allows the customized conda environment to be shared with co-workers?
  • A. odsc conda install
  • B. odsc conda modify
  • C. odsc conda clone
  • D. odsc conda publish
Answer: D
Explanation:
Detailed Answer in Step-by-Step Solution:
* Objective: Share a custom conda environment in OCI Data Science.
* Understand Commands: OCI provides odsc CLI for environment management.
* Evaluate Options:
* A: clone duplicates an environment locally-not for sharing.
* B: publish uploads the environment to Object Storage for team access-correct.
* C: modify doesn't exist as a standard command.
* D: install sets up an environment locally-not for sharing.
* Reasoning: Sharing requires publishing to a shared location (Object Storage), which publish achieves.
* Conclusion: B is the correct command.
The OCI Data Science CLI documentation states: "Use odsc conda publish to package and upload a custom conda environment to an Object Storage Bucket, making it accessible to other users." clone (A) is for local duplication, modify (C) isn't valid, and install (D) is for local setup-not sharing. B is the designated sharing mechanism.
Oracle Cloud Infrastructure Data Science CLI Reference, "odsc conda publish".

NEW QUESTION # 32
The feature type TechJob has the following registered validators:
* TechJob.validator.register(name='is_tech_job', handler=is_tech_job_default_handler)
* TechJob.validator.register(name='is_tech_job', handler=is_tech_job_open_handler, condition= ('job_family',))
* TechJob.validator.register(name='is_tech_job', handler=is_tech_job_closed_handler, condition= ('job_family': 'IT'))When you run is_tech_job(job_family='Engineering'), what does the feature type validator system do?
  • A. Execute the is_tech_job_open_handler handler
  • B. Execute the is_tech_job_closed_handler handler
  • C. Throw an error because the system cannot determine which handler to run
  • D. Execute the is_tech_job_default_handler handler
Answer: A
Explanation:
Detailed Answer in Step-by-Step Solution:
* Objective: Determine which validator handler runs for is_tech_job(job_family='Engineering').
* Understand Validator System: Likely ADS SDK-executes handlers based on conditions.
* Analyze Validators:
* Default: is_tech_job_default_handler-No condition, fallback.
* Open: is_tech_job_open_handler-Condition ('job_family',)-requires job_family arg.
* Closed: is_tech_job_closed_handler-Condition ('job_family': 'IT')-requires job_family='IT'.
* Evaluate Call: job_family='Engineering'-Matches job_family presence, not IT.
* Reasoning:
* Open handler applies (tuple condition means arg exists).
* Closed fails (Engineering # IT).
* Default is overridden by specific matches.
* Conclusion: D is correct.
OCI ADS documentation states: "Validators execute the most specific handler matching the condition; for is_tech_job(job_family='Engineering'), is_tech_job_open_handler (D) runs as it matches job_family presence, while is_tech_job_closed_handler (C) requires IT-default (A) is bypassed, no error (B)." Only D fits per ADS validator logic.
Oracle Cloud Infrastructure ADS SDK Documentation, "Feature Type Validators".

NEW QUESTION # 33
What is a conda environment?
  • A. A system that manages package dependencies
  • B. An environment deployment system on Oracle AI
  • C. A collection of kernels
  • D. An open-source environment management system
Answer: D
Explanation:
Detailed Answer in Step-by-Step Solution:
* Define Conda: Conda is a widely used tool for managing packages and environments in data science.
* Evaluate Options:
* A: Partially true-Conda manages dependencies, but it's broader (an environment system).
* B: Incorrect-Kernels (e.g., Jupyter) are separate; Conda manages environments.
* C: Correct-Conda is an open-source tool for creating isolated environments with specific packages.
* D: Incorrect-Not specific to Oracle AI; it's a general tool.
* Reasoning: C captures Conda's full scope as an open-source system, beyond just dependency management (A).
* Conclusion: C is the most accurate.
OCI documentation describes Conda as "an open-source package and environment management system that allows data scientists to create isolated environments with specific versions of Python and libraries." A is too narrow, B misaligns with kernel concepts, and D ties it incorrectly to Oracle AI. C aligns with Conda's official definition and OCI's usage.
Oracle Cloud Infrastructure Data Science Documentation, "Conda Environments Overview".

NEW QUESTION # 34
You want to create an anomaly detection model using the OCI Anomaly Detection service that avoids as many false alarms as possible. False Alarm Probability (FAP) indicates model performance. How would you set the value of the False Alarm Probability?
  • A. Low
  • B. Zero
  • C. Use a function
  • D. High
Answer: A
Explanation:
Detailed Answer in Step-by-Step Solution:
* Objective: Minimize false alarms in OCI Anomaly Detection.
* Understand FAP: False Alarm Probability-lower FAP means fewer false positives.
* Evaluate Options:
* A: High FAP-Increases false alarms-incorrect.
* B: Low FAP-Reduces false alarms-correct.
* C: Zero FAP-Unrealistic; risks missing true anomalies.
* D: Function-Vague, not a direct setting.
* Reasoning: Low FAP balances sensitivity and false positives- aligns with goal.
* Conclusion: B is correct.
OCI Anomaly Detection documentation states: "Set a low False Alarm Probability (FAP) to minimize false positives, though too low (e.g., zero) may miss anomalies." B fits the goal-high (A) increases errors, zero (C) is impractical, and function (D) isn't specified.
Oracle Cloud Infrastructure Anomaly Detection Documentation, "Configuring FAP".

NEW QUESTION # 35
Which is NOT a part of Observability and Management Services?
  • A. OCI Management Service
  • B. Logging Analytics
  • C. Event Services
  • D. Logging
Answer: A
Explanation:
Detailed Answer in Step-by-Step Solution:
* Objective: Identify the non-Observability and Management (O&M) service in OCI.
* Understand O&M: Includes monitoring, logging, events tools.
* Evaluate Options:
* A: Event Services-Triggers actions, part of O&M-correct.
* B: OCI Management Service-Not a defined O&M service-incorrect.
* C: Logging Analytics-Log analysis, O&M component-correct.
* D: Logging-Log collection, O&M component-correct.
* Reasoning: B isn't listed in OCI's O&M suite-others are.
* Conclusion: B is correct (not part of O&M).
OCI documentation lists "Observability and Management Services as including Event Services (A), Logging Analytics (C), and Logging (D)-'OCI Management Service' (B) is not a recognized component." B appears to be a misnomer-only A, C, D are O&M per OCI's service catalog.
Oracle Cloud Infrastructure Observability and Management Documentation, "Service Overview".

NEW QUESTION # 36
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