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Oracle 1Z0-1110-26 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Implement End-to-End Machine Learning Lifecycle | 45% | - Use AutoML and built-in algorithms - Model development, training, and evaluation - Data preparation, exploration, and transformation - Model saving, cataloging, and versioning - Deploy models and manage endpoints |
| Apply MLOps Practices | 20% | - ML pipelines, automation, and reproducibility - Governance, auditing, and compliance - Model monitoring, drift detection, and performance tracking |
| OCI Data Science - Introduction & Configuration | 10% | - Tenancy and environment configuration for Data Science - Overview and core concepts of OCI Data Science - Capabilities of the Accelerated Data Science (ADS) SDK |
| Design and Set Up Data Science Workspace | 15% | - Create and manage projects and notebook sessions - Configure compute shapes, storage, and networking - Manage access control, security, and IAM integration |
| Integrate Related OCI Services | 10% | - Integration with OCI Object Storage, Vault, and Networking - Use OCI AI and data services with Data Science |
Oracle Cloud Infrastructure Data Science Professional Sample Questions:
1. 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_in_notebook()
B) show_corr()
C) to_xgb()
D) compute()
2. When preparing your model artifact to save it to the Oracle Cloud Infrastructure (OCI) DataScience model catalog, you create a score.py file. What is the purpose of the score.py file?
A) Define the inference server dependencies
B) Execute the inference logic code
C) Configure the deployment infrastructure
D) Define the compute scaling strategy
3. Which architecture is based on the principle of “never trust, always verify”?
A) Defense in depth
B) Federated identity
C) Zero trust
D) Fluid perimeter
4. You want to use ADSTuner to tune the hyperparameters of a supported model you recently trained. You have just started your search and want to reduce the computational cost as well as assess the quality of the model class that you are using. What is the most appropriate search space strategy to choose?
A) ADSTuner doesn’t need a search space to tune the hyperparameters
B) Detailed
C) Pass a dictionary that defines a search space
D) Perfunctory
5. What is the correct definition of Git?
A) Git is a distributed version control system that allows you to track changes made to a set of files.
B) Git is a centralized version control system that allows you to revert to previous versions of files as needed.
C) Git is a centralized version control system that allows data scientists and developers to track copious amounts of data.
D) Git is a distributed version control system that protects teams from simultaneous repo contributions and merge requests.
Solutions:
| Question # 1 Answer: A | Question # 2 Answer: B | Question # 3 Answer: C | Question # 4 Answer: D | Question # 5 Answer: A |
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