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Updated: Sep 17, 2026
No. of Questions: 58 Questions & Answers with Testing Engine
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To prepare for the Oracle 1z0-1110-22 certification exam, professionals should have a strong background in data science and machine learning. They should also have experience working with the Oracle Cloud Infrastructure platform and be familiar with best practices for developing data science solutions. To prepare for the exam, professionals can take advantage of a range of study materials, including online courses, practice exams, and study guides.
| Certification Vendor: | Oracle |
|---|---|
| Exam Name: | Oracle Cloud Infrastructure Data Science 2022 Professional |
| Exam Number: | 1Z0-1110-22 |
| Certificate Validity Period: | 24 months |
| Passing Score: | 64% - 65% |
| Available Languages: | English |
| Exam Format: | Multiple Select, Scenario-Based, Multiple Choice |
| Real Exam Qty: | 55 - 58 |
| Exam Price: | USD 245 |
| Exam Duration: | 90 minutes |
| Related Certifications: | Oracle Cloud Infrastructure Certified Professional |
| Recommended Training: | Become an OCI Data Science Professional OCI Learning Subscription |
| Exam Registration: | Pearson VUE Oracle Education |
| Sample Questions: | Oracle 1z0-1110-22 Sample Questions |
| Exam Way: | Online proctored or at Pearson VUE authorized test centers |
| Pre Condition: | No mandatory prerequisites; recommended familiarity with Python, SQL, machine learning concepts, and basic OCI infrastructure |
| Official Syllabus URL: | https://education.oracle.com/oracle-cloud-infrastructure-data-science-2022-professional |
Oracle 1z0-1110-22 certification is ideal for data scientists, data engineers, and machine learning professionals who want to validate their proficiency in implementing cloud-based data science solutions. 1z0-1110-22 exam is intended to test your ability to use Oracle Cloud Infrastructure services to build scalable, secure, and performant data science solutions. By earning this certification, you can demonstrate to potential employers that you have the knowledge and skills necessary to design, develop, and manage data science projects on the Oracle Cloud Infrastructure platform.
Oracle 1z0-1110-22 exam covers a wide range of topics, including machine learning algorithms, data preparation and feature engineering, model training and evaluation, and model deployment and monitoring. Candidates will be tested on their ability to design and implement end-to-end data science solutions using the tools and services available on Oracle Cloud Infrastructure. They must also demonstrate their proficiency in using programming languages such as Python and SQL, as well as their ability to work with big data technologies such as Apache Spark.
Oracle 1z0-1110-22 (Oracle Cloud Infrastructure Data Science 2022 Professional) Exam is a certification exam designed for professionals who work with data science in the Oracle Cloud Infrastructure (OCI) environment. 1z0-1110-22 exam is intended to validate a candidate's knowledge and skills in various areas of data science, including data preparation, modeling, deployment, and monitoring. 1z0-1110-22 exam also covers topics related to OCI data science services, such as Autonomous Database and Data Flow.
| Section | Weight | Objectives |
|---|---|---|
| Integration with OCI Services | 15% | - OCI Logging, Monitoring and IAM - OCI AI Services integration - OCI Data Flow for large-scale processing - OCI Functions and serverless inference |
| Model Deployment and MLOps | 20% | - Model Catalog usage - A/B testing and lifecycle management - Model monitoring and versioning - Deploying models as REST endpoints |
| API, SDK and Automation | 15% | - Python SDK usage - OCI Data Science REST API - Workflow automation |
| Model Development and AutoML | 20% | - Working with JupyterLab and Conda environments - Training and optimizing models - Model evaluation and validation - Using Oracle AutoML |
| OCI Data Science Service Overview and Architecture | 15% | - Core concepts and features - Tenancy configuration and setup - Service architecture and components |
| Data Storage, Preparation and Management | 15% | - Data labeling and dataset creation - Data integration with OCI storage services - Data versioning and lifecycle management |
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