[Oct 04, 2025] New Real 1z0-1110-25 Exam Dumps Questions [Q50-Q73]

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[Oct 04, 2025] New Real 1z0-1110-25 Exam Dumps Questions

Pass Your 1z0-1110-25 Exam Easily with Accurate Oracle Cloud Infrastructure 2025 Data Science Professional PDF Questions

Oracle 1z0-1110-25 Exam Syllabus Topics:

Topic Details
Topic 1
  • 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 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
  • 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
  • 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.

 

Q50. You want to make your model more frugal to reduce the cost of collecting and processing data. You plan to do this by removing features that are highly correlated. You would like to create a heatmap that displays the correlation so that you can identify candidate features to remove. Which Accelerated Data Science (ADS) SDK method is appropriate to display the comparability between Continuous and Categorical features?

 
 
 
 

Q51. When preparing your model artifact to save it to the Oracle Cloud Infrastructure (OCI) DataScience model catalog, you create a score.py file. What is the purpose of the score.py file?

 
 
 
 

Q52. As a data scientist for a hardware company, you have been asked to predict the revenue demand for the upcoming quarter. You develop a time series forecasting model to analyze the data. Select the correct sequence of steps to predict the revenue demand values for the upcoming quarter.

 
 
 
 

Q53. True or false? Bias is a common problem in data science applications.

 
 

Q54. You are a data scientist trying to load data into your notebook session. You understand that Accelerated Data Science (ADS) SDK supports loading various data formats. Which of the following THREE are ADS- supported data formats?

 
 
 
 
 

Q55. Where do calls to stdout and stderr from score.py go in a model deployment?

 
 
 
 

Q56. Which activity is NOT a part of the machine learning life cycle?

 
 
 
 

Q57. You are a data scientist using Oracle AutoML to produce a model and you are evaluating the score metric for the model. Which of the following TWO prevailing metrics would you use for evaluating a multiclass classification model?

 
 
 
 
 

Q58. As a data scientist, you are tasked with creating a model training job that is expected to take different hyperparameter values on every run. What is the most efficient way to set those parameters with Oracle Data Science Jobs?

 
 
 
 

Q59. You have a complex Python code project that could benefit from using Data Science Jobs as it is a repeatable machine learning model training task. The project contains many sub-folders and classes. What is the best way to run this project as a Job?

 
 
 
 

Q60. You have created a model and want to use Accelerated Data Science (ADS) SDK to deploy the model. Where are the artifacts to deploy this model with ADS?

 
 
 
 

Q61. You are a data scientist with a set of text and image files that need annotation, and you want to use Oracle Cloud Infrastructure (OCI) Data Labeling. Which of the following THREE annotation classes are supported by the tool?

 
 
 
 
 
 

Q62. Which technique can be used for feature engineering in the machine learning lifecycle?

 
 
 
 

Q63. Which Oracle Accelerated Data Science (ADS) classes can be used for easy access to datasets from reference libraries and index websites such as scikit-learn?

 
 
 
 

Q64. You are a data scientist leveraging the Oracle Cloud Infrastructure (OCI) Language AI service for various types of text analyses. Which TWO capabilities can you utilize with this tool?

 
 
 
 
 

Q65. As a data scientist, you are working on a global health dataset that has data from more than 50 countries. You want to encode three features, such as ‘countries’, ‘race’, and ‘body organ’ as categories. Which option would you use to encode the categorical feature?

 
 
 
 

Q66. You are asked to prepare data for a custom-built model that requires transcribing Spanish video recordings into a readable text format with profane words identified. Which Oracle Cloud Service would you use?

 
 
 
 

Q67. You realize that your model deployment is about to reach its utilization limit. What would you do to avoid the issue before requests start to fail? Pick THREE.

 
 
 
 
 

Q68. You have received machine learning model training code, without clear information about the optimal shape to run the training. How would you proceed to identify the optimal compute shape for your model training that provides a balanced cost and processing time?

 
 
 
 

Q69. Which statement accurately describes an aspect of machine learning models?

 
 
 
 

Q70. You have received machine learning model training code, without clear information about the optimal shape to run the training on. How would you proceed to identify the optimal compute shape for your model training that provides a balanced cost and processing time?

 
 
 
 

Q71. As a data scientist, you use the Oracle Cloud Infrastructure (OCI) Language service to train custommodels.
Which types of custom models can be trained?

 
 
 
 

Q72. 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?

 
 
 
 

Q73. You loaded data into Oracle Cloud Infrastructure (OCI) Data Science. To transform the data, you want to use the Accelerated Data Science (ADS) SDK. When you applied the get_recommendations() tool to the ADSDataset object, it showed you user-detected issues with all the recommended changes to apply to the dataset. Which option should you use to apply all the recommended transformations at once?

 
 
 
 

Updated 1z0-1110-25 Exam Practice Test Questions: https://www.braindumpspass.com/Oracle/1z0-1110-25-practice-exam-dumps.html

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