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Oracle 1Z0-1110-26 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Implement End-to-End Machine Learning Lifecycle | – Save and manage models using Model Catalog – Automate machine learning workflows and pipelines – Prepare and manage datasets – Deploy models and consume model endpoints – Build, train, and evaluate machine learning models |
| Apply MLOps Practices | – Implement model lifecycle management – Use best practices for operationalizing ML solutions – 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 – Configure and manage Data Science resources – Understand OCI Data Science service concepts and architecture |
| 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 |
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