Oracle 1Z0-1110-26 Exam Overview:
| Certification Vendor: | Oracle |
|---|---|
| Exam Name: | Oracle Cloud Infrastructure Data Science Professional |
| Exam Number: | 1Z0-1110-26 |
| Real Exam Qty: | 50 |
| Available Languages: | English |
| Exam Format: | Multiple Choice |
| Certificate Validity Period: | 24 months |
| Passing Score: | 68% |
| Exam Duration: | 90 minutes |
| Exam Price: | USD 245 |
| Recommended Training: | Oracle Cloud Infrastructure Data Science Professional Course Become an OCI Data Science Professional (2026) |
| Exam Registration: | Oracle University Exam Page Oracle MyLearn Registration |
| Sample Questions: | Oracle 1Z0-1110-26 Sample Questions |
| Exam Way: | Online proctored or in-person at authorized testing centers |
| Pre Condition: | No mandatory prerequisites; recommended: proficiency in Python and ML concepts, 6+ months hands-on OCI experience, familiarity with open-source data science libraries |
| Official Syllabus URL: | https://education.oracle.com/oracle-cloud-infrastructure-data-science-professional/pexam_1Z0-1110-26 |
Oracle 1Z0-1110-26 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Integrate Related OCI Services | 10% | - Use OCI AI and data services with Data Science - Integration with OCI Object Storage, Vault, and Networking |
| Apply MLOps Practices | 20% | - Model monitoring, drift detection, and performance tracking - ML pipelines, automation, and reproducibility - Governance, auditing, and compliance |
| Implement End-to-End Machine Learning Lifecycle | 45% | - Data preparation, exploration, and transformation - Use AutoML and built-in algorithms - Model saving, cataloging, and versioning - Deploy models and manage endpoints - Model development, training, and evaluation |
| OCI Data Science - Introduction & Configuration | 10% | - Overview and core concepts of OCI Data Science - Capabilities of the Accelerated Data Science (ADS) SDK - Tenancy and environment configuration for Data Science |
| Design and Set Up Data Science Workspace | 15% | - Create and manage projects and notebook sessions - Manage access control, security, and IAM integration - Configure compute shapes, storage, and networking |
Oracle Cloud Infrastructure Data Science Professional Sample Questions:
Question 1
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?
A. Start with the strongest compute shape Jobs support and monitor the job run metrics and time required to complete the model training. Tune the model so that it utilizes as much compute resources as possible, even at an increased cost.
B. Start with a small shape and monitor the utilization metrics and time required to complete the model training. If the compute shape is fully utilized, change to compute that has more resources and rerun the job. Repeat the process until the processing time does not improve.
C. Start with a random compute shape and monitor the utilization metrics and time required to finish the model training. Perform model training optimization and performance tests in advance to identify the right compute shape before running the model training as a job.
D. Start with a smaller shape and monitor the job run metrics and time required to complete the model training. If the compute shape is not fully utilized, tune the model parameters, and rerun the job. Repeat the process until the shape resources are fully utilized.
Question 2
You have just started as a data scientist at a healthcare company. You have been asked to analyze and improve a deep neural network model, which was built based on the electrocardiogram records of patients. There are no details about the model framework that was built. What would be the best way to find more details about the machine learning models inside the model catalog?
A. Refer to the code inside the model
B. Check for provenance details
C. Check for metadata tags
D. Check for model taxonomy details
Question 3
True or false? Data scientists typically need a combination of technical skills, nontechnical ones, and suitable personality traits to be successful.
A. True
B. False
Question 4
You want to make your model more frugal to reduce the cost of collecting and processing dat a. 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?
A. cramersv_plot()
B. correlation_ratio_plot()
C. pearson_plot()
D. corr()
Question 5
Which statement is true about standards?
A. They may be audited
B. They are the foundation of corporate governance
C. They are the result of a regulation or contractual requirement or an industry requirement
D. They are methods and instructions on how to maintain or accomplish the directives of the policy
Solutions:
| Question 1 Answer: B | Question 2 Answer: B | Question 3 Answer: A | Question 4 Answer: B | Question 5 Answer: A |


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