1z0-1110-25 PDF Exam Material 2026 Realistic 1z0-1110-25 Dumps Questions [Q31-Q53]

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1z0-1110-25 PDF Exam Material 2026 Realistic 1z0-1110-25 Dumps Questions

Updated Oracle 1z0-1110-25 Dumps – PDF & Online Engine

QUESTION 31
You have built a machine model to predict whether a bank customer is going to default on a loan. You want to use Local Interpretable Model-Agnostic Explanations (LIME) to understand a specific prediction. What is the key idea behind LIME?

 
 
 
 

QUESTION 32
Which of these protects customer data at rest and in transit in a way that allows customers to meet their security and compliance requirements for cryptographic algorithms and key management?

 
 
 
 

QUESTION 33
Which OCI service provides a managed Kubernetes service for deploying, scaling, and managing containerized applications?

 
 
 
 

QUESTION 34
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?

 
 
 
 

QUESTION 35
In machine learning, what is the primary difference between supervised and unsupervised learning?

 
 
 
 

QUESTION 36
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?

 
 
 
 

QUESTION 37
You are a data scientist working inside a notebook session and you attempt to pip install a package from a public repository that is not included in your conda environment. After running this command, you get a network timeout error. What might be missing from your network configuration?

 
 
 
 

QUESTION 38
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?

 
 
 
 

QUESTION 39
Where do calls to stdout and stderr from score.py go in a model deployment?

 
 
 
 

QUESTION 40
You are a data scientist; you use the Oracle Cloud Infrastructure (OCI) Language service to train custom models. Which types of custom models can be trained?

 
 
 
 

QUESTION 41
As a data scientist, you use the Oracle Cloud Infrastructure (OCI) Language service to train custommodels.
Which types of custom models can be trained?

 
 
 
 

QUESTION 42
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?

 
 
 
 

QUESTION 43
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?

 
 
 
 
 
 

QUESTION 44
Which THREE types of data are used for Data Labeling?

 
 
 
 

QUESTION 45
Which model has an open-source, open model format that allows you to run machine learning models on different platforms?

 
 
 
 

QUESTION 46
Which type of file system does File Storage use?

 
 
 
 

QUESTION 47
What is the minimum active storage duration for logs used by Logging Analytics to be archived?

 
 
 
 

QUESTION 48
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.

 
 
 
 

QUESTION 49
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?

 
 
 
 

QUESTION 50
You want to make your model more parsimonious 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 would be appropriate to display the correlation between Continuous and Categorical features?

 
 
 
 

QUESTION 51
You have created a conda environment in your notebook session. This is the first time you are working with published conda environments. You have also created an Object Storage bucket with permission to manage the bucket. Which TWO commands are required to publish the conda environment?

 
 
 
 
 

QUESTION 52
In which two ways can you improve data durability in Oracle Cloud Infrastructure Object Storage?

 
 
 
 
 

QUESTION 53
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?

 
 
 
 

Oracle 1z0-1110-25 Exam Syllabus Topics:

Topic Details
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
  • 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 3
  • 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 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
  • 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.

 

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