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Oracle Oracle Cloud 1Z0-1110-26

1Z0-1110-26

Exam Code: 1Z0-1110-26

Exam Name: Oracle Cloud Infrastructure Data Science Professional

Updated: Jul 18, 2026

Q & A: 160 Questions and Answers

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Oracle 1Z0-1110-26 Exam Syllabus Topics:

SectionObjectives
Apply MLOps Practices- Use best practices for operationalizing ML solutions
- Implement model lifecycle management
- Monitor and maintain machine learning models
Design and Set Up Data Science Workspace- Use Accelerated Data Science SDK and open source tools
- Create and configure Data Science projects
- Manage notebook sessions and compute resources
OCI Data Science - Introduction and Configuration- Use OCI Data Science notebooks and sessions
- Understand OCI Data Science service concepts and architecture
- Configure and manage Data Science resources
Use Related OCI Services- Integrate OCI Data and AI services
- Apply OCI services for data ingestion, storage, and processing
- Design machine learning solutions for business use cases
Implement End-to-End Machine Learning Lifecycle- Deploy models and consume model endpoints
- Automate machine learning workflows and pipelines
- Save and manage models using Model Catalog
- Prepare and manage datasets
- Build, train, and evaluate machine learning models

Oracle Cloud Infrastructure Data Science Professional Sample Questions:

1. Which of these options allow the sharing and loading back of ML models into a notebook session?

A) Model deployment
B) Model catalog
C) Model provenance
D) Model taxonomy


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

A) True
B) False


3. 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?

A) Create a new job by setting the required parameters in your code and create a new job for every code change
B) Create your code to expect different parameters as command-line arguments and create a new job every time you run the code
C) Create a new job every time you need to run your code and pass the parameters as environment variables
D) Create your code to expect different parameters either as environment variables or as command-line arguments, which are set on every job run with different values


4. 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) Adaptive sampling, Algorithm selection, Feature selection, Hyperparameter tuning
C) Adaptive sampling, Feature selection, Algorithm selection, Hyperparameter tuning
D) Algorithm selection, Feature selection, Adaptive sampling, Hyperparameter tuning


5. 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?

A) Object detection, Text classification
B) Text classification, Named Entity Recognition (NER)
C) Sentiment Analysis, Named Entity Recognition (NER)
D) Image classification, Named Entity Recognition (NER)


Solutions:

Question # 1
Answer: B
Question # 2
Answer: A
Question # 3
Answer: D
Question # 4
Answer: C
Question # 5
Answer: B

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