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Oracle 1Z0-1110-26 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Topic 1: Design and Set Up Data Science Workspace | - Use Accelerated Data Science SDK and open source tools - Manage notebook sessions and compute resources - Create and configure Data Science projects |
| Topic 2: OCI Data Science - Introduction and Configuration | - Use OCI Data Science notebooks and sessions - Understand OCI Data Science service concepts and architecture - Configure and manage Data Science resources |
| Topic 3: Use Related OCI Services | - Integrate OCI Data and AI services - Design machine learning solutions for business use cases - Apply OCI services for data ingestion, storage, and processing |
| Topic 4: Apply MLOps Practices | - Implement model lifecycle management - Use best practices for operationalizing ML solutions - Monitor and maintain machine learning models |
| Topic 5: Implement End-to-End Machine Learning Lifecycle | - Build, train, and evaluate machine learning models - Deploy models and consume model endpoints - Save and manage models using Model Catalog - Automate machine learning workflows and pipelines - Prepare and manage datasets |
Oracle Cloud Infrastructure Data Science Professional Sample Questions:
Which OCI service provides a managed Kubernetes service for deploying, scaling, and managing containerized applications?
- A. Oracle Cloud Infrastructure Streaming
- B. Oracle Cloud Infrastructure Container Engine for Kubernetes
- C. Oracle Cloud Infrastructure Load Balancing
- D. Oracle Cloud Infrastructure Container Registry
Correct Answer: B 🗳️
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Which technique can be used for feature engineering in the machine learning lifecycle?
- A. Gradient boosting
- B. Principal Component Analysis (PCA)
- C. Support Vector Machines (SVM)
- D. K-means clustering
Correct Answer: B 🗳️
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You have received machine learning model training code, without clear information about the optimal shape to run the training. How would you proceed to identify the optimal compute shape for your model training that provides a balanced cost and processing time?
- A. Start with a random compute shape and monitor the utilization metrics and time required to finish the model training. Perform model training optimizations and performance tests in advance to identify the right compute shape before running the model training as a job
- B. Start with a smaller shape and monitor the Job Run metrics and time required to complete the model training. If the compute shape is not fully utilized, tune the model parameters, and rerun the job. Repeat the process until the shape resources are fully utilized
- C. Start with a smaller shape and monitor the utilization metrics and time required to complete the model training. If the compute shape is fully utilized, change to compute that has more resources and rerun the job. Repeat the process until the processing time does not improve
- D. Start with the strongest compute shape Jobs support and monitor the Job Run metrics and time required to complete the model training. Tune the model so that it utilizes as much compute resources as possible, even at an increased cost
Correct Answer: C 🗳️
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You have been given a collection of digital files required for a business audit. They consist of several different formats that you would like to annotate using Oracle Cloud Infrastructure (OCI) Data Labeling. Which THREE types of files could this tool annotate?
- A. Images of computer server racks
- B. Video footage of a conversation in a conference room
- C. A typewritten document that details an annual budget
- D. An audio recording of a phone conversation
- E. A collection of purchase orders for office supplies
Correct Answer: A,B,C 🗳️
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Which of the following best describes the principal goal of data science?
- A. To collect and archive exhaustive datasets from various source systems for corporate record-keeping uses.
- B. To mine and analyze large amounts of data in order to uncover information that can be used for operational improvements and business gains.
- C. Data science is focused on output of the analysis.
- D. To collect and prepare data for use as part of analytics applications.
Correct Answer: B 🗳️
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