Exam Name: Oracle Cloud Infrastructure Data Science Professional
Certification Provider: Oracle
Corresponding Certification: Oracle Cloud
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Oracle 1Z0-1110-26 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Topic 1: Design and Set Up Data Science Workspace | - Manage notebook sessions and compute resources - Use Accelerated Data Science SDK and open source tools - Create and configure Data Science projects |
| Topic 2: OCI Data Science - Introduction and Configuration | - Use OCI Data Science notebooks and sessions - Configure and manage Data Science resources - Understand OCI Data Science service concepts and architecture |
| Topic 3: Apply MLOps Practices | - Use best practices for operationalizing ML solutions - Implement model lifecycle management - Monitor and maintain machine learning models |
| Topic 4: Implement End-to-End Machine Learning Lifecycle | - Save and manage models using Model Catalog - Build, train, and evaluate machine learning models - Prepare and manage datasets - Deploy models and consume model endpoints - Automate machine learning workflows and pipelines |
| Topic 5: Use Related OCI Services | - Design machine learning solutions for business use cases - Apply OCI services for data ingestion, storage, and processing - Integrate OCI Data and AI services |
Oracle Cloud Infrastructure Data Science Professional Sample Questions:
Which step is unique to MLOps, as opposed to DevOps?
- A. Continuous delivery
- B. Continuous deployment
- C. Continuous training
- D. Continuous integration
Correct Answer: C 🗳️
Explanation: Only visible for PrepAwayExam members. You can sign-up / login (it's free).
You want to evaluate the relationship between feature values and target variables. You have a large number of observations having a near uniform distribution and the features are highly correlated. Which model explanation technique should you choose?
- A. Feature Dependence Explanations
- B. Feature Permutation Importance Explanations
- C. Local Interpretable Model-Agnostic Explanations
- D. Accumulated Local Effects
Correct Answer: D 🗳️
Explanation: Only visible for PrepAwayExam members. You can sign-up / login (it's free).
You are working as a data scientist for a healthcare company. They decide to analyze the data to find patterns in a large volume of electronic medical records. You are asked to build a PySpark solution to analyze these records in a JupyterLab notebook. What is the order of recommended stepsto develop a PySpark application in Oracle Cloud Infrastructure (OCI) Data Science?
- A. Configure core-site.xml, install a PySpark conda environment, create a Data Flow application with the Accelerated Data Science (ADS) SDK, develop your PySpark application, launch a notebook session
- B. Launch a notebook session, configure core-site.xml, install a PySpark conda environment, develop your PySpark application, create a Data Flow application with the Accelerated Data Science (ADS) SDK
- C. Install a Spark conda environment, configure core-site.xml, launch a notebook session, create a Data Flow application with the Accelerated Data Science (ADS) SDK, develop your PySpark application
- D. Launch a notebook session, install a PySpark conda environment, configure core-site.xml, develop your PySpark application, create a Data Flow application with the Accelerated Data Science (ADS) SDK
Correct Answer: D 🗳️
Explanation: Only visible for PrepAwayExam members. You can sign-up / login (it's free).
Which is NOT a compliance document?
- A. Attestation
- B. Certificate
- C. Penetration test report
- D. Bridge letter
Correct Answer: C 🗳️
Explanation: Only visible for PrepAwayExam members. You can sign-up / login (it's free).
You want to make your model more frugal to reduce the cost of collecting and processing dat a. You plan to do this by removing features that are highly correlated. You would like to create a heatmap 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. pearson_plot()
- D. cramersv_plot()
Correct Answer: B 🗳️
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