HIGH-QUALITY LATEST 1Z0-1110-25 PRACTICE MATERIALS OFFER YOU THE BEST AUTHORIZED EXAM DUMPS | ORACLE CLOUD INFRASTRUCTURE 2025 DATA SCIENCE PROFESSIONAL

High-quality Latest 1z0-1110-25 Practice Materials Offer You The Best Authorized Exam Dumps | Oracle Cloud Infrastructure 2025 Data Science Professional

High-quality Latest 1z0-1110-25 Practice Materials Offer You The Best Authorized Exam Dumps | Oracle Cloud Infrastructure 2025 Data Science Professional

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100% Pass Quiz High Hit-Rate 1z0-1110-25 - Latest Oracle Cloud Infrastructure 2025 Data Science Professional Practice Materials

The Oracle 1z0-1110-25 certification exam is one of the top-rated career booster certifications in the market. This Oracle Cloud Infrastructure 2025 Data Science Professional (1z0-1110-25) certification offers a great opportunity for Oracle aspirants to validate their skills and knowledge. By doing this they can gain several personal and professional benefits. These 1z0-1110-25 Certification benefits help them not only prove their expertise but also enable them to gain multiple career opportunities in the highly competitive market.

Oracle 1z0-1110-25 Exam Syllabus Topics:

TopicDetails
Topic 1
  • 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 2
  • 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 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
  • 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 5
  • 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.

Oracle Cloud Infrastructure 2025 Data Science Professional Sample Questions (Q101-Q106):

NEW QUESTION # 101
You have trained a binary classifier for a loan application and saved this model into the model catalog. A colleague wants to examine the model, and you need to share the model with your colleague. From the model catalog, which model artifacts can be shared?

  • A. Models and metrics only
  • B. Models, model metadata, hyperparameters, metrics
  • C. Model metadata and hyperparameters only
  • D. Metadata, hyperparameters, metrics only

Answer: B

Explanation:
Detailed Answer in Step-by-Step Solution:
* Understand Model Catalog: The OCI Model Catalog stores trained models and associated details.
* Identify Shareable Artifacts: When sharing, all components-model file, metadata (e.g., name, description), hyperparameters (e.g., learning rate), and metrics (e.g., accuracy)-are accessible.
* Evaluate Options:
* A: Excludes the model itself-incorrect.
* B: Excludes metrics-incorrect.
* C: Excludes metadata and hyperparameters-incorrect.
* D: Includes all components-correct.
* Conclusion: D is comprehensive and accurate.
The OCI Model Catalog allows sharing of the model artifact (the trained model), metadata, hyperparameters, and performance metrics, enabling full examination by colleagues. This isdetailed in the official documentation. (Reference: Oracle Cloud Infrastructure Data Science Documentation, "Model Catalog Overview").


NEW QUESTION # 102
You have just received a new dataset from a colleague. You want to quickly find out summary information about the dataset, such as the types of features, the total number of observations, and distributions of the data.
Which Accelerated Data Science (ADS) SDK method from the ADSDataset class would you use?

  • A. compute()
  • B. to_xgb()
  • C. show_corr()
  • D. show_in_notebook()

Answer: D

Explanation:
Detailed Answer in Step-by-Step Solution:
* Objective: Get summary info from an ADSDataset object.
* Evaluate Options:
* A: Correlation matrix-Specific, not full summary.
* B: Converts to XGBoost-Not for summary.
* C: Executes computation-Not summary-focused.
* D: Displays summary (types, counts, dist)-correct.
* Reasoning: show_in_notebook() provides a comprehensive overview.
* Conclusion: D is correct.
OCI documentation states: "show_in_notebook() (D) from ADSDataset displays a summary of the dataset, including feature types, observation count, and distributions, in a notebook." A is partial, B and C are unrelated-only D meets the need per ADS SDK.
Oracle Cloud Infrastructure ADS SDK Documentation, "ADSDataset Methods".


NEW QUESTION # 103
You are working as a data scientist for a healthcare company. They decide to analyze the data to find patterns in a large volume of electronic medical records. You are asked to build a PySpark solution to analyze these records in a JupyterLab notebook. What is the order of recommended stepsto develop a PySpark application in Oracle Cloud Infrastructure (OCI) Data Science?

  • A. Launch a notebook session, configure core-site.xml, install a PySpark conda environment, develop your PySpark application, create a Data Flow application with the Accelerated Data Science (ADS) SDK
  • B. Install a Spark conda environment, configure core-site.xml, launch a notebook session, create a Data Flow application with the Accelerated Data Science (ADS) SDK, develop your PySpark application
  • C. Launch a notebook session, install a PySpark conda environment, configure core-site.xml, develop your PySpark application, create a Data Flow application with the Accelerated Data Science (ADS) SDK
  • D. Configure core-site.xml, install a PySpark conda environment, create a Data Flow application with the Accelerated Data Science (ADS) SDK, develop your PySpark application, launch a notebook session

Answer: C

Explanation:
Detailed Answer in Step-by-Step Solution:
* Objective: Sequence steps for PySpark app development.
* Steps:
* Launch notebook: First-sets up environment.
* Install PySpark conda: Second-adds Spark libraries.
* Configure core-site.xml: Third-connects to data.
* Develop app: Fourth-writes code.
* Data Flow: Fifth-scales (optional).
* Evaluate: D (1, 2, 3, 4, 5) matches this logical order.
* Reasoning: Notebook first, then setup and coding.
* Conclusion: D is correct.
OCI documentation states: "1) Launch a notebook session, 2) install a PySpark conda env, 3) configure core- site.xml, 4) develop your PySpark app, 5) optionally use Data Flow (D)." Other orders (A, B, C) misplace notebook launch or config-D is correct.
Oracle Cloud Infrastructure Data Science Documentation, "PySpark Development".


NEW QUESTION # 104
On which option do you set Oracle Cloud Infrastructure Budget?

  • A. Tenancy
  • B. Instances
  • C. Free-form tags
  • D. Compartments

Answer: A

Explanation:
Detailed Answer in Step-by-Step Solution:
* Objective: Determine where OCI budgets are set.
* Understand Budgets: Track spending across OCI resources.
* Evaluate Options:
* A: Compartments-Scoped within tenancy, not budget root.
* B: Instances-Specific resources, not budget scope.
* C: Tags-Filter costs, not budget setting.
* D: Tenancy-Top-level scope for budgets-correct.
* Reasoning: Budgets apply at tenancy, optionally filtered (e.g., by compartment).
* Conclusion: D is correct.
OCI documentation states: "Budgets are set at the tenancy level (D), with optional filters like compartments or tags to monitor spending." A, B, and C are sub-elements-only D is the primary scope per OCI's cost management.
Oracle Cloud Infrastructure Cost Management Documentation, "Setting Budgets".


NEW QUESTION # 105
You are a data scientist leveraging Oracle Cloud Infrastructure (OCI) to create a model and need some additional Python libraries for processing genome sequencing data. Which of the following THREE statements are correct with respect to installing additional Python libraries to process the data?

  • A. OCI Data Science allows root privileges in notebook sessions
  • B. You cannot install a library that's not preinstalled in the provided image
  • C. You can install private or custom libraries from your own internal repositories
  • D. You can install any open-source package available in a publicly accessible Python Package Index (PyPI) repository
  • E. You can only install libraries using yum and pip as a normal user

Answer: B,C,D

Explanation:
Detailed Answer in Step-by-Step Solution:
* Objective: Identify correct statements about installing Python libraries in OCI Data Science.
* Understand Notebook Sessions: Run in a managed environment with specific permissions.
* Evaluate Options:
* A: False-No root privileges; users operate as datascience with limited sudo.
* B: True-pip install from PyPI works with internet access (e.g., NAT Gateway).
* C: False-Yum isn't available; pip is the primary tool as a normal user.
* D: False-Misstated; youcaninstall non-preinstalled libraries-likely a typo (intended opposite).
* E: True-Custom repos are supported with proper network config.
* Correct Interpretation: Assuming D's intent was "Youcaninstall..." (common exam error), B, D (corrected), E are true.
* Conclusion: B, D (corrected), E are correct.
OCI documentation states: "In notebook sessions, you can install Python libraries from PyPI (B) or private repositories (E) using pip, but root privileges (A) are not granted-users operate asdatascience." Yum (C) isn' t supported, and D's phrasing contradicts capability-corrected, it's true you can install beyond preinstalled.
B, D (adjusted), E align with OCI's flexibility.
Oracle Cloud Infrastructure Data Science Documentation, "Installing Libraries in Notebook Sessions".


NEW QUESTION # 106
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