Oracle 1z0-1110-23 : Oracle Cloud Infrastructure Data Science 2023 Professional

  • Exam Code: 1z0-1110-23
  • Exam Name: Oracle Cloud Infrastructure Data Science 2023 Professional
  • Updated: Sep 23, 2026   Q&As: 80 Questions and Answers

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About Oracle 1z0-1110-23 Exam

Knowing the material is half the exam; the other half is the room. The Oracle Cloud Infrastructure Data Science 2023 Professional test engine from DumpsTests simulates the real 1z0-1110-23 environment, so the 80 questions you practiced feel familiar under pressure.

Oracle 1z0-1110-23 Exam Overview:
Certification Vendor:Oracle
Exam Name:Oracle Cloud Infrastructure Data Science 2023 Professional
Exam Number:1Z0-1110-23
Real Exam Qty:55
Related Certifications:Oracle Cloud Infrastructure 2023 Professional Certifications
Exam Duration:90 minutes
Certificate Validity Period:18 months
Exam Format:Multiple Choice, Multiple Select
Passing Score:65%
Available Languages:English
Exam Price:USD $245
Recommended Training:Become an OCI Data Science Professional (2023)
OCI Data Science Workshop
Exam Registration:Oracle Education
Pearson VUE Registration
Sample Questions:Free Download 1z0-1110-23 Exam PDF Torrent
Exam Way:Online proctored or Onsite testing at Pearson VUE centers
Pre Condition:No mandatory prerequisites; recommended basic knowledge of OCI, Python, and machine learning concepts
Official Syllabus URL:https://education.oracle.com/oracle-cloud-infrastructure-data-science-2023-professional/pexam_1Z0-1110-23
Oracle 1z0-1110-23 Exam Syllabus Topics:
SectionWeightObjectives
Topic 1: Model Evaluation, Explanation, and Catalog15%- Compare and select optimal models
- Generate global and local model explanations
- Register and manage models in the Model Catalog
- Evaluate model performance and metrics
Topic 2: Accelerated Data Science (ADS) SDK and AutoML20%- Tune hyperparameters and optimize models
- Implement automated ML workflows with Oracle AutoML
- Perform feature engineering and selection
- Utilize ADS SDK libraries and functionality
Topic 3: Model Development, Training, and Jobs20%- Create and run notebook sessions
- Configure and manage custom training jobs
- Manage source code and version control
- Use OCI Data Flow for distributed Spark applications
Topic 4: Model Deployment, MLOps, and Monitoring15%- Implement MLOps practices for lifecycle management
- Monitor model performance, logs, and drift
- Build and run ML pipelines
- Deploy models as REST endpoints
Topic 5: Data Access, Preparation, and Labeling15%- Perform data exploration and profiling
- Access data from OCI Object Storage, Database, and other sources
- Export datasets for model development
- Use OCI Data Labeling service to create annotated datasets
Topic 6: OCI Data Science Overview and Configuration15%- Integrate with OCI IAM and networking
- Design and set up workspaces, projects, and environments
- Manage access, policies, and security settings
- Understand OCI Data Science concepts and architecture

Your Oracle 1z0-1110-23 Questions, Answered

The Oracle Cloud Infrastructure Data Science 2023 Professional blueprint divides into 6 domains — including Model Evaluation, Explanation, and Catalog (15%), Data Access, Preparation, and Labeling (15%), OCI Data Science Overview and Configuration (15%). Those weights tell you where the points live; plan revision time in the same proportions. The full subtopic list appears above.

No mandatory prerequisites; recommended basic knowledge of OCI, Python, and machine learning concepts Eligibility rules change occasionally, so confirm them on the official page (official 1z0-1110-23 exam page) before booking.

Yes — the free Oracle Cloud Infrastructure Data Science 2023 Professional demo at DumpsTests shows real questions and answers before you pay. Every purchase includes 365 days of free updates, renewable later at 50% off.

The official format: 90 minutes, 55 questions. That ratio is the real challenge, so practice pacing — time-box each question, mark the stubborn ones, and run full simulations in the DumpsTests PC test engine until the clock stops being scary.

Yes:

Classroom learning ends where self-testing begins — after any course, work through the 80 practice questions for the Oracle Cloud Infrastructure Data Science 2023 Professional to find weak spots before the exam does.

The Oracle Cloud Infrastructure Data Science 2023 Professional is Oracle's official exam for the Oracle Cloud Infrastructure 2023 Certified Data Science Professional credential (Professional level). In the job market it works as portable proof of skill — more interviews, better offers. It pairs naturally with Oracle Cloud Infrastructure 2023 Professional Certifications.

Two promises. Delivery: payment triggers an automatic email within a minute — instant download, unlimited devices, 24/7 help if nothing arrives within 2 hours. Refund: take the corresponding 1z0-1110-23 exam within 60 days of purchase, and if you fail, send a scanned enrollment slip plus the official Score Report PDF within 2 days of the exam for a full refund, processed within 7 days. Excluded: exams within 3 days of purchase, candidate names that don't match the payer, and free or expired products. Prefer a swap? Exchange for two equal-value products free.

Register through the vendor's official channels:

The Oracle Cloud Infrastructure Data Science 2023 Professional is delivered Online proctored or Onsite testing at Pearson VUE centers — choose whichever suits you when booking.

USD $245 per attempt; 65% to pass. Since a retake bills the full fee again, rehearse with the 80 practice questions from DumpsTests until your mock scores clear the bar with room to spare.

Oracle Cloud Infrastructure Data Science 2023 Professional Sample Questions:
Question #1

Which two statements are true about published conda environments?

  • A. Your notebook session acts as the source to share published conda environments with team members.
  • B. You can only create a published conda environment by modifying a Data Science conda environment.
  • C. In addition to service job run environment variables, conda environment variables can be used in Data Science Jobs.
  • D. The odac conda init command is used to configure the location of published conda environments.
  • E. They are curated by Oracle Cloud Infrastructure (OCI) Data Science.
Reveal Solution  Discussion  0

Correct Answer: A,C  🗳️

Question #2

Using Oracle AutoML, you are tuning hyperparameters on a supported model class and have specified a time budget. AutoML terminates computation once the time budget is exhausted. What would you expect AutoML to return in case the time budget is exhausted before hyperparameter tuning is completed?

  • A. The last generated hyperparameter configuration is returned
  • B. A hyperparameter configuration with a minimum learning rate is returned.
  • C. A random hyperparameter configuration is returned.
  • D. The current best-known hyperparameter configuration is returned.
Reveal Solution  Discussion  0

Correct Answer: D  🗳️

Question #3

You want to make your model more frugal to reduce the cost of collecting and processing data.
You plan to do this by removing features that are highly correlated. You would like to create a heat map 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. corr()
  • B. correlation_ratio_plot()
  • C. cramersv_plot()
  • D. pearson_plot()
Reveal Solution  Discussion  0

Correct Answer: B  🗳️

Question #4

The Oracle AutoML pipeline automates hyperparameter tuning by training the model with different parameters in parallel. You have created an instance of Oracle AutoML as ora-cle_automl and now you want an output with all the different trials performed by Oracle Au-toML. Which of the following command gives you the results of all the trials?

  • A. Oracle.automl.visualize_tuning_trails()
  • B. Oracle.automl.visualize_algorith_selection_trails()
  • C. Oracle.automl.visualize_adaptive_sampling_trails()
  • D. Oracle.automl.print_trials()
Reveal Solution  Discussion  0

Correct Answer: D  🗳️

Question #5

As a data scientist, you create models for cancer prediction based on mammographic images.
The correct identification is very crucial in this case. After evaluating two models, you arrive at the following confusion matrix.
Model 1 has Test accuracy is 80% and recall is 70%.
* Model 2 has Test accuracy is 75% and recall is 85%.
Which model would you prefer and why?

  • A. Model 2, because recall has more impact on predictions in this use se.
  • B. Model 1, because the test accuracy is high.
  • C. Model 1, because recall has lesser impact on predictions in this use case
  • D. Model 2, because recall is high.
Reveal Solution  Discussion  0

Correct Answer: A  🗳️

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