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Oracle 1Z0-1110-26 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Implement End-to-End Machine Learning Lifecycle | - Build, train, and evaluate machine learning models - Save and manage models using Model Catalog - Deploy models and consume model endpoints - Automate machine learning workflows and pipelines - Prepare and manage datasets |
| Apply MLOps Practices | - Monitor and maintain machine learning models - Use best practices for operationalizing ML solutions - Implement model lifecycle management |
| 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 |
| OCI Data Science - Introduction and Configuration | - Configure and manage Data Science resources - Understand OCI Data Science service concepts and architecture - Use OCI Data Science notebooks and sessions |
| Design and Set Up Data Science Workspace | - Create and configure Data Science projects - Manage notebook sessions and compute resources - Use Accelerated Data Science SDK and open source tools |
Oracle Cloud Infrastructure Data Science Professional Sample Questions:
Question 1
As a data scientist for a hardware company, you have been asked to predict the revenue demand for the upcoming quarter. You develop a time series forecasting model to analyze the dat a. Select the correct sequence of steps to predict the revenue demand values for the upcoming quarter.
A. Prepare model, verify, save, deploy, predict
B. Prepare model, deploy, verify, save, predict
C. Verify, prepare model, deploy, save, predict
D. Predict, deploy, save, verify, prepare model
Question 2
Which function's objective is to represent the difference between the predictive value and the target value?
A. Cost function
B. Update function
C. Fit function
D. Optimizer function
Question 3
Which of the following best describes the principal goal of data science?
A. To mine and analyze large amounts of data in order to uncover information that can be used for operational improvements and business gains.
B. To collect and archive exhaustive datasets from various source systems for corporate record-keeping uses.
C. To collect and prepare data for use as part of analytics applications.
D. Data science is focused on output of the analysis.
Question 4
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. Model metadata and hyperparameters only
B. Models, model metadata, hyperparameters, metrics
C. Models and metrics only
D. Metadata, hyperparameters, metrics only
Question 5
Which of these is a unique feature of the published conda environment?
A. Provides a comprehensive environment to solve business use cases
B. Provides availability on network session reactivation
C. Allows you to save the conda environment to an Object Storage Bucket
D. Allows you to save the conda environment in a block volume
Solutions:
| Question 1 Answer: A | Question 2 Answer: A | Question 3 Answer: A | Question 4 Answer: B | Question 5 Answer: C |
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