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Oracle 1Z0-1110-26 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Implement End-to-End Machine Learning Lifecycle | 45% | - Deploy models and manage endpoints - Use AutoML and built-in algorithms - Data preparation, exploration, and transformation - Model development, training, and evaluation - Model saving, cataloging, and versioning |
| Design and Set Up Data Science Workspace | 15% | - Configure compute shapes, storage, and networking - Create and manage projects and notebook sessions - Manage access control, security, and IAM integration |
| Apply MLOps Practices | 20% | - Governance, auditing, and compliance - ML pipelines, automation, and reproducibility - Model monitoring, drift detection, and performance tracking |
| Integrate Related OCI Services | 10% | - Integration with OCI Object Storage, Vault, and Networking - Use OCI AI and data services with Data Science |
| OCI Data Science - Introduction & Configuration | 10% | - Tenancy and environment configuration for Data Science - Capabilities of the Accelerated Data Science (ADS) SDK - Overview and core concepts of OCI Data Science |
Oracle Cloud Infrastructure Data Science Professional Sample Questions:
1. You are a data scientist working inside a notebook session and you attempt to pip install a package from a public repository that is not included in your conda environment. After running this command, you get a network timeout error. What might be missing from your networking configuration?
A) FastConnect to an on-premises network
B) NAT Gateway with public internet access
C) Primary Virtual Network Interface Card (VNIC)
D) Service Gateway with private subnet access
2. You are preparing a configuration object necessary to create a Data Flow application. Which THREE parameter values should you provide?
A) The compartment of the Data Flow application
B) The display name of the application
C) The local path to your PySpark script
D) The path to the archive.zip file
E) The bucket used to read/write the PySpark script in Object Storage
3. You are a data scientist working for a manufacturing company. You have developed a forecasting model to predict the sales demand in the upcoming months. You created a model artifact that contained custom logic requiring third-party libraries. When you deployed the model, it failed to run because you did not include all the third-party dependencies in the model artifact. What file should be modified to include the missing libraries?
A) requirements.txt
B) model_artifact_validate.py
C) score.py
D) runtime.yaml
4. You have just received a new dataset from a colleague. You want to quickly find out summary information about the dataset, such as the types of features, the total number of observations, and distributions of the dat a. Which Accelerated Data Science (ADS) SDK method from the ADSDataset class would you use?
A) show_corr()
B) compute()
C) show_in_notebook()
D) to_xgb()
5. You have trained a binary classifier for a loan application and saved this model into the model catalog. A colleague wants to examine the model, and you need to share the model with your colleague. From the model catalog, which model artifacts can be shared?
A) Models, model metadata, hyperparameters, metrics
B) Model metadata and hyperparameters only
C) Metadata, hyperparameters, metrics only
D) Models and metrics only
Solutions:
| Question # 1 Answer: B | Question # 2 Answer: A,B,E | Question # 3 Answer: D | Question # 4 Answer: C | Question # 5 Answer: A |



