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Oracle 1Z0-1110-26 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Integrate Related OCI Services | 10% | - Integration with OCI Object Storage, Vault, and Networking - Use OCI AI and data services with Data Science |
| Topic 2: Apply MLOps Practices | 20% | - ML pipelines, automation, and reproducibility - Model monitoring, drift detection, and performance tracking - Governance, auditing, and compliance |
| Topic 3: Design and Set Up Data Science Workspace | 15% | - Create and manage projects and notebook sessions - Manage access control, security, and IAM integration - Configure compute shapes, storage, and networking |
| Topic 4: OCI Data Science - Introduction & Configuration | 10% | - Capabilities of the Accelerated Data Science (ADS) SDK - Tenancy and environment configuration for Data Science - Overview and core concepts of OCI Data Science |
| Topic 5: Implement End-to-End Machine Learning Lifecycle | 45% | - Data preparation, exploration, and transformation - Deploy models and manage endpoints - Model development, training, and evaluation - Use AutoML and built-in algorithms - Model saving, cataloging, and versioning |
Oracle Cloud Infrastructure Data Science Professional Sample Questions:
1. You are working in your notebook session and find that your notebook session does not have enough compute CPU and memory for your workload. How would you scale up your notebook session without losing your work?
A) Download your files and data to your local machine, delete your notebook session, provision a new notebook session on a larger compute shape, and upload your files from your local machine to the new notebook session
B) Create a temporary bucket in Object Storage, write all your files and data to Object Storage, delete the notebook session, provision a new notebook session on a larger compute shape, and copy your files and data from your temporary bucket to your new notebook session
C) Ensure your files and environments are written to the block volume storage under the /home/datascience directory, deactivate the notebook session, and activate the notebook with a larger compute shape selected
D) Deactivate your notebook session, provision a new notebook session on a larger compute shape, and recreate all your file changes
2. What is the primary difference between a data scientist and a data engineer?
A) A data engineer creates data flows to be used as templates by the data analyst.
B) A data engineer builds data pipelines and helps prepare data, while a data scientist is responsible for data collection, preparation, and analysis.
C) A data engineer collects and prepares data, and a data scientist then analyzes it.
D) A data engineer analyzes data after a data scientist collects and prepares it.
3. What is the correct definition of Git?
A) Git is a distributed version control system that protects teams from simultaneous repo contributions and merge requests.
B) Git is a distributed version control system that allows you to track changes made to a set of files.
C) Git is a centralized version control system that allows you to revert to previous versions of files as needed.
D) Git is a centralized version control system that allows data scientists and developers to track copious amounts of data.
4. Which type of firewalls are designed to protect against web application attacks, such as SQL injection and cross-site scripting?
A) Stateful inspection firewall
B) Web Application Firewall
C) Packet filtering firewall
D) Incident firewall
5. Which of these protects customer data at rest and in transit in a way that allows customers to meet their security and compliance requirements for cryptographic algorithms and key management?
A) Identity Federation
B) Customer isolation
C) Security controls
D) Data encryption
Solutions:
| Question # 1 Answer: C | Question # 2 Answer: C | Question # 3 Answer: B | Question # 4 Answer: B | Question # 5 Answer: D |
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