Oracle Cloud Infrastructure 2025 Data Science Professional Certification: Complete Guide 2026
1Z0-1110-25
The Oracle Cloud Infrastructure 2025 Data Science Professional certification validates expertise in implementing machine learning solutions, managing data science workflows, and deploying models using OCI Data Science services.
Exam Details
Resources
Everything you need to pass
Comprehensive preparation materials for your Oracle Cloud Infrastructure 2025 Data Science Professional exam
Exam Content
Exam Domains & Topics
Master these 4 domains to pass your exam
OCI Data Science Service
Machine Learning Model Development
Model Deployment and Management
Data Engineering and MLOps
Who Should Take This Exam?
- Data scientists with cloud computing experience
- Machine learning engineers transitioning to OCI
- Analytics professionals seeking to validate ML expertise
- Cloud architects specializing in data science workloads
Study Timeline
10-14 weeks
Recommended duration
Foundation · Weeks 1-2
Review exam objectives & core concepts
Deep Dive · Weeks 3-6
Study each domain with hands-on labs
Practice & Review · Weeks 7-8
Take practice exams & target weak areas
Study Guide
1Z0-1110-25 Study Plan
The Oracle Cloud Infrastructure 2025 Data Science Professional certification (1Z0-1110-25) validates your expertise in using OCI Data Science services, developing and deploying machine learning models, and implementing MLOps practices. This professional-level certification demonstrates your ability to architect and implement end-to-end data science solutions on Oracle Cloud Infrastructure.
Week 1-2
OCI Fundamentals and Data Science Service Basics
Build foundational knowledge of OCI and get familiar with the Data Science service
- Complete OCI fundamentals training
- Set up OCI free tier account and create first Data Science project
- Navigate the OCI console and understand IAM concepts
- Create and manage notebook sessions with different compute shapes
- Install and configure ADS SDK
Week 3-4
Deep Dive into OCI Data Science Features
Master all components of the OCI Data Science service
- Work with conda environments and create custom environments
- Practice with Model Catalog - save, load, and version models
- Understand Data Science Jobs and create scheduled pipelines
- Configure networking and security for Data Science projects
- Explore ADS SDK features for data loading and model management
Week 5-6
Machine Learning Model Development
Build comprehensive ML models using various algorithms and techniques
- Implement classification, regression, and clustering models
- Practice feature engineering and selection techniques
- Perform hyperparameter tuning using multiple strategies
- Use AutoML features in ADS SDK
- Implement model explainability with SHAP and LIME
- Work with imbalanced datasets and evaluation metrics
Week 7-8
Model Deployment and Serving
Learn to deploy, manage, and monitor ML models in production
- Create model artifacts with all dependencies
- Deploy models using OCI Model Deployment service
- Test deployed models via REST API endpoints
- Configure scaling and resource allocation
- Implement model monitoring and logging
- Practice A/B testing scenarios
Week 9-10
Data Engineering and MLOps Implementation
Build end-to-end MLOps pipelines with automation
- Create data ingestion pipelines from multiple sources
- Build automated model training pipelines using Jobs
- Implement CI/CD for ML models
- Configure automated retraining triggers
- Practice with feature stores and data versioning
- Integrate multiple OCI services in workflows
Week 11
Integration and Advanced Topics
Master advanced features and service integrations
- Practice deep learning workflows with TensorFlow and PyTorch
- Implement NLP and computer vision projects
- Integrate with OCI Functions and API Gateway
- Optimize costs and resource utilization
- Review security and compliance best practices
Week 12
Review and Practice Exams
Consolidate knowledge and prepare for exam day
- Review all exam domains and identify weak areas
- Take multiple practice exams
- Review incorrect answers and understand gaps
- Create summary notes for quick reference
- Practice time management with timed quizzes
Study tips
Hands-on Practice is Critical
- Create an OCI Free Tier account immediately and use it throughout your study
- Build at least 5-10 complete ML projects from data ingestion to deployment
- Practice every feature of the Data Science service, not just reading about them
- Create notebook sessions with different compute shapes to understand configurations
- Deploy multiple models and test them via REST APIs
Master the ADS SDK
- The Accelerated Data Science SDK is central to OCI Data Science - know it thoroughly
- Practice all ADS functions: model saving, loading, evaluation, and explanation
- Understand how ADS integrates with the Model Catalog
- Learn ADS methods for data loading from Object Storage and databases
- Familiarize yourself with ADS AutoML capabilities and configurations
Understand Service Integration
- Learn how Data Science integrates with Object Storage, ADW, and other OCI services
- Practice creating end-to-end pipelines using multiple services
- Understand IAM policies required for Data Science service access
- Know how to configure VCN and networking for Data Science projects
- Practice integrating with OCI Functions and API Gateway for model serving
Focus on MLOps and Production Patterns
- Understand the complete model lifecycle from development to retirement
- Practice creating automated training and deployment pipelines
- Learn model monitoring, logging, and alerting strategies
- Know different deployment patterns (batch vs real-time, A/B testing)
- Understand when to retrain models and how to automate it
Study Model Development Thoroughly
- Don't just memorize algorithms - understand when to use each one
- Practice feature engineering techniques on real datasets
- Know various evaluation metrics and which to use for different problems
- Understand hyperparameter tuning strategies and their trade-offs
- Learn model explainability methods and how to implement them in OCI
Documentation is Your Friend
- Bookmark all relevant OCI documentation pages for quick reference
- Read through the entire Data Science service documentation at least twice
- Review API references for common operations
- Study architecture diagrams and reference architectures
- Keep release notes and new features documentation handy
Time Management During Study
- Allocate 30% of time to OCI Data Science service specifics
- Spend 25% each on ML development and deployment topics
- Dedicate 20% to data engineering and MLOps
- Reserve last 2 weeks for review and practice exams
- Create summary notes after each study session for quick review
Practice Exam Strategy
- Take at least 3 full-length practice exams under timed conditions
- Review all incorrect answers thoroughly - understand why you got them wrong
- Identify patterns in questions - certain topics may appear frequently
- Time yourself: 55 questions in 90 minutes = less than 2 minutes per question
- Practice eliminating obviously wrong answers first
Exam day checklist
- Arrive 15 minutes early if taking exam at a test center, or prepare your space 30 minutes before for online proctoring
- Read each question carefully - some may have multiple correct answers with one being 'most correct'
- Watch for keywords like 'best practice', 'most efficient', 'least expensive', 'most secure'
- If unsure, eliminate obviously wrong answers first, then make an educated guess
- Flag difficult questions and return to them after completing easier ones
- You need 38 correct answers out of 55 to pass (68%) - don't panic if some questions seem very difficult
- OCI-specific questions often focus on service limits, pricing models, and best practices
- For scenario questions, identify the core requirement before selecting an answer
- Don't spend more than 2 minutes on any single question - move on and come back if needed
- Review all flagged questions if time permits before submitting the exam
- Remember that hands-on experience is the best preparation - real-world scenarios help immensely
- Stay calm and confident - you've prepared thoroughly with hands-on practice
Career
Career Opportunities
Roles and salary potential for Oracle Cloud Infrastructure 2025 Data Science Professional certified professionals
Related Job Titles
$135,000
Average Annual Salary
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Prerequisites
Strong understanding of machine learning concepts and algorithms Experience with Python programming and data science libraries Familiarity with Oracle Cloud Infrastructure fundamentals Practical experience with model development and deployment
Oracle Cloud Infrastructure 2025 Data Science Professional FAQs
Common questions about the 1Z0-1110-25 certification exam
This certification validates your ability to use OCI Data Science services to build, train, deploy, and manage machine learning models in production environments. It demonstrates expertise in end-to-end ML workflows including data preparation, model development, deployment strategies, and MLOps best practices on Oracle Cloud Infrastructure.
The exam is considered advanced-level and requires both theoretical knowledge of machine learning concepts and practical experience with OCI Data Science services. Candidates should have hands-on experience building and deploying ML models, proficiency in Python, and familiarity with OCI infrastructure. Most candidates need 10-14 weeks of preparation combining training courses and practical lab work.
Professionals with the Oracle Cloud Infrastructure Data Science Professional certification typically earn between $120,000 and $150,000 annually, with an average salary around $135,000. Salaries vary based on experience level, geographic location, company size, and additional skills in AI/ML technologies. Senior data scientists with this certification can command salaries exceeding $160,000.
About the Oracle Cloud Infrastructure 2025 Data Science Professional Certification
The Oracle Cloud Infrastructure 2025 Data Science Professional (1Z0-1110-25) is a professional-level certification offered by Oracle. This certification validates your expertise in data & analytics and is recognized globally by employers seeking qualified professionals. The exam consists of 55 questions to be completed in 90 minutes, with a passing score of 68%. The exam fee is $245, and the certification is valid for Does not expire.
Why Get Oracle Cloud Infrastructure 2025 Data Science Professional Certified?
- Career Advancement: Certified professionals earn an average of $135,000 per year. Oracle-certified professionals are among the most sought-after in the data & analytics industry.
- Industry Recognition: Oracle certifications are respected worldwide by employers, demonstrating verified competency in data & analytics technologies and practices.
- Skill Validation: The Oracle Cloud Infrastructure 2025 Data Science Professional exam rigorously tests your knowledge across 4 domains, ensuring you have the practical skills employers demand.
Oracle Cloud Infrastructure 2025 Data Science Professional Exam Format & Details
The 1Z0-1110-25 exam is designed to test both theoretical knowledge and practical application. Candidates are given 90 minutes to complete the exam, which contains approximately 55 questions. A score of 68% is required to pass. As a professional-level exam, it requires significant hands-on experience and deep technical knowledge. Prerequisites include: Strong understanding of machine learning concepts and algorithms Experience with Python programming and data science libraries Familiarity with Oracle Cloud Infrastructure fundamentals Practical experience with model development and deployment.
Exam Domains & Topics
The Oracle Cloud Infrastructure 2025 Data Science Professional exam covers 4 key domains. Understanding the weight of each domain helps you allocate your study time effectively:
- OCI Data Science Service (30% of exam)
- Machine Learning Model Development (25% of exam)
- Model Deployment and Management (25% of exam)
- Data Engineering and MLOps (20% of exam)
Who Should Take the Oracle Cloud Infrastructure 2025 Data Science Professional Exam?
This certification is designed for professionals in the following roles:
- Data scientists with cloud computing experience
- Machine learning engineers transitioning to OCI
- Analytics professionals seeking to validate ML expertise
- Cloud architects specializing in data science workloads
Career Opportunities & Salary
Earning the Oracle Cloud Infrastructure 2025 Data Science Professional certification opens doors to roles such as Data Scientist, Machine Learning Engineer, AI Solutions Architect, Cloud Data Science Specialist. Certified professionals earn an average salary of $135,000 per year, reflecting the high demand for data & analytics skills in today's job market.
Recertification & Renewal
The Oracle Cloud Infrastructure 2025 Data Science Professional certification is valid for Does not expire. To maintain your credential, you will need to meet Oracle's renewal requirements before your certification expires. This may include earning continuing education credits, passing a recertification exam, or earning a higher-level certification.
Exam Registration & Cost
The 1Z0-1110-25 exam costs $245. You can register through Oracle's official website or an authorized testing center. Most candidates choose between in-person testing at a Pearson VUE or PSI center and online proctored exams taken from home. Be sure to review the exam policies, including identification requirements and prohibited items, before your test date.
How to Prepare for 1Z0-1110-25
We recommend 10-14 weeks of dedicated study time to prepare for the Oracle Cloud Infrastructure 2025 Data Science Professional exam. Start by reviewing the official exam objectives, then work through each domain systematically. Regular practice with exam-style questions is essential for building confidence and identifying weak areas. Combine reading with hands-on practice to develop both theoretical knowledge and practical skills.
HydraNode publishes free exam dumps with answers and explanations for more than 80 certification exams. Every question is written to the published objectives, so what you practise matches the format and difficulty of the actual 1Z0-1110-25 exam.