- 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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| Section | Objectives |
|---|---|
| Design and Set Up Data Science Workspace | - Manage notebook sessions and compute resources - Create and configure Data Science projects - Use Accelerated Data Science SDK and open source tools |
| Use Related OCI Services | - Apply OCI services for data ingestion, storage, and processing - Integrate OCI Data and AI services - Design machine learning solutions for business use cases |
| Implement End-to-End Machine Learning Lifecycle | - Prepare and manage datasets - Build, train, and evaluate machine learning models - Automate machine learning workflows and pipelines - Deploy models and consume model endpoints - Save and manage models using Model Catalog |
| 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 |
| Apply MLOps Practices | - Implement model lifecycle management - Use best practices for operationalizing ML solutions - Monitor and maintain machine learning models |
1. You want to use ADSTuner to tune the hyperparameters of a supported model you recently trained. You have just started your search and want to reduce the computational cost as well as assess the quality of the model class that you are using. What is the most appropriate search space strategy to choose?
A) Perfunctory
B) Pass a dictionary that defines a search space
C) ADSTuner doesn’t need a search space to tune the hyperparameters
D) Detailed
2. You’re going to create an Oracle Cloud Infrastructure Anomaly Detection model for multivariate dat a. Where do you need to store the training data?
A) Your local machine
B) Autonomous Data Warehouse
C) Object Storage Bucket
D) MySQL database
3. You are a data scientist working for a manufacturing company. You have developed a forecasting model to predict the sales demand in the upcoming months. You created a model artifact that contained custom logic requiring third-party libraries. When you deployed the model, it failed to run because you did not include all the third-party dependencies in the model artifact. What file should be modified to include the missing libraries?
A) runtime.yaml
B) requirements.txt
C) score.py
D) model_artifact_validate.py
4. 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? Which THREE steps would you perform?
A) Update the deployment to use a larger virtual machine (more CPUs/memory)
B) Update the deployment to add more instances
C) Delete the deployment
D) Update the deployment to use fewer instances
E) Reduce the load balancer bandwidth limit so that fewer requests come in
5. Where do calls to stdout and stderr from score.py go in a model deployment?
A) The OCI Cloud Shell, which can be accessed from the console
B) The OCI console
C) The predict log in the Oracle Cloud Infrastructure (OCI) Logging service as defined in the deployment
D) The file that was defined for them on the Virtual Machine (VM)
Solutions:
| Question # 1 Answer: A | Question # 2 Answer: C | Question # 3 Answer: A | Question # 4 Answer: A,B,E | Question # 5 Answer: C |
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