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Oracle 1Z0-1110-26 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Design and Set Up Data Science Workspace | 15% | - Configure compute shapes, storage, and networking - Manage access control, security, and IAM integration - Create and manage projects and notebook sessions |
| Implement End-to-End Machine Learning Lifecycle | 45% | - Data preparation, exploration, and transformation - Model development, training, and evaluation - Use AutoML and built-in algorithms - Model saving, cataloging, and versioning - Deploy models and manage endpoints |
| Apply MLOps Practices | 20% | - ML pipelines, automation, and reproducibility - Model monitoring, drift detection, and performance tracking - Governance, auditing, and compliance |
| 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 |
| Integrate Related OCI Services | 10% | - Use OCI AI and data services with Data Science - Integration with OCI Object Storage, Vault, and Networking |
Oracle Cloud Infrastructure Data Science Professional Sample Questions:
Question 1
For your next data science project, you need access to public geospatial images. Which Oracle Cloud service provides free access to those images?
A. Oracle Open Data
B. Oracle Cloud Infrastructure (OCI) Data Science
C. Oracle Analytics Cloud
D. Oracle Big Data Service
Question 2
You are building a model and need input that represents data as morning, afternoon, or evening. However, the data contains a timestamp. What part of the Data Science lifecycle would you be in when creating the new variable?
A. Model validation
B. Feature engineering
C. Data access
D. Model type selection
Question 3
You have built a machine model to predict whether a bank customer is going to default on a loan. You want to use Local Interpretable Model-Agnostic Explanations (LIME) to understand a specific prediction. What is the key idea behind LIME?
A. Local explanation techniques are model-agnostic, while global explanation techniques are not
B. Global behaviour of a machine learning model may be complex, while the local behaviour may be approximated with a simpler surrogate model
C. Global and local behaviours of machine learning models are similar
D. Model-agnostic techniques are more interpretable than techniques that are dependent on the types of models
Question 4
You are asked to prepare data for a custom-built model that requires transcribing Spanish video recordings into a readable text format with profane words identified. Which Oracle Cloud Service would you use?
A. OCI Speech
B. OCI Translation
C. OCI Language
D. OCI Anomaly Detection
Question 5
What is a common maxim about data scientists?
A. They spend 80% of their time analyzing data and 20% finding and preparing it.
B. They spend 80% of their time finding and preparing data and 20% analyzing it.
C. They spend 80% of their time on failed analytics projects and 20% doing useful work.
Solutions:
| Question 1 Answer: A | Question 2 Answer: B | Question 3 Answer: B | Question 4 Answer: A | Question 5 Answer: B |
