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Oracle 1Z0-1110-26 Exam Syllabus Topics:

Section	Weight	Objectives
Machine Learning Fundamentals	20%	- Unsupervised learning 1. Clustering 2. Dimensionality reduction - Supervised learning 1. Regression 2. Classification
OCI Data Science Service	30%	- Projects and notebooks 1. Conda environments 2. Notebook sessions - Model catalog 1. Model metadata 2. Model versioning
MLOps and OCI Integration	20%	- Automation and pipelines 1. Model lifecycle management 2. CI/CD integration - OCI ecosystem 1. Object Storage 2. IAM and security
Model Development and Deployment	30%	- Model deployment 1. Prediction endpoints 2. Deployment creation - Model training 1. Experiments 2. Hyperparameter optimization

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Oracle Cloud Infrastructure Data Science Professional Sample Questions (Q98-Q103):

NEW QUESTION # 98
On which option do you set Oracle Cloud Infrastructure Budget?

A. Compartments
B. Tenancy
C. Free-form tags
D. Instances

Answer: B

Explanation:
Detailed Answer in Step-by-Step Solution:
Objective: Determine where OCI budgets are set.
Understand Budgets: Track spending across OCI resources.
Evaluate Options:
A: Compartments—Scoped within tenancy, not budget root.
B: Instances—Specific resources, not budget scope.
C: Tags—Filter costs, not budget setting.
D: Tenancy—Top-level scope for budgets—correct.
Reasoning: Budgets apply at tenancy, optionally filtered (e.g., by compartment).
Conclusion: D is correct.
OCI documentation states: “Budgets are set at the tenancy level (D), with optional filters like compartments or tags to monitor spending.” A, B, and C are sub-elements—only D is the primary scope per OCI’s cost management.
1: Oracle Cloud Infrastructure Cost Management Documentation, "Setting Budgets".

NEW QUESTION # 99
In machine learning, what is the primary difference between supervised and unsupervised learning?

A. Supervised learning is only used for image recognition, while unsupervised learning can be used for various analytics applications.
B. Supervised learning is created and managed by the Data Engineer.
C. Supervised learning is monitored closely by data scientists, while they don’t play a role inunsupervised learning.
D. Supervised learning involves data that has been labeled and classified, while unsupervised learning data is unlabeled and unclassified.

Answer: D

Explanation:
Detailed Answer in Step-by-Step Solution:
Objective: Identify the key difference between supervised and unsupervised learning.
Define Types:
Supervised: Uses labeled data (e.g., input-output pairs) to predict outcomes.
Unsupervised: Uses unlabeled data to find patterns (e.g., clustering).
Evaluate Options:
A: Labeled vs. unlabeled—Core distinction, correct.
B: Monitoring—Misleading, not the primary difference.
C: Image recognition—False, supervised applies broadly.
D: Data Engineer—Irrelevant to learning type.
Reasoning: A captures the foundational data difference.
Conclusion: A is correct.
OCI documentation states: “Supervised learning uses labeled data to train models for prediction, while unsupervised learning analyzes unlabeled data to discover patterns.” B, C, and D misrepresent this—only A aligns with OCI’s ML definitions and industry standards.
1: Oracle Cloud Infrastructure Data Science Documentation, "Machine Learning Types".

NEW QUESTION # 100
Which two statements are true about published conda environments?

A. Your notebook session acts as the source to share published conda environments with team members
B. The odsc conda init command is used to configure the location of published conda environments
C. They are curated by Oracle Cloud Infrastructure (OCI) Data Science
D. You can only create a published conda environment by modifying a Data Science conda environment
E. In addition to service job run environment variables, conda environment variables can be used inData Science Jobs

Answer: B,E

Explanation:
Detailed Answer in Step-by-Step Solution:
Objective: Identify true statements about published conda environments in OCI.
Understand Published Conda: Custom envs shared via Object Storage.
Evaluate Options:
A: False—Users create them, not OCI-curated.
B: True—odsc conda init sets up access to published envs.
C: False—Object Storage, not notebook, is the source.
D: False—Can create from scratch, not just modifications.
E: True—Conda env vars extend job configs.
Reasoning: B configures access, E enhances flexibility—match OCI behavior.
Conclusion: B and E are correct.
OCI documentation states: “odsc conda init (B) configures the bucket for published conda environments, and Jobs can use conda environment variables (E) alongside service vars.” A misattributes curation, C misplaces source, and D limits creation—only B and E are true per OCI’s conda management.
1: Oracle Cloud Infrastructure Data Science Documentation, "Published Conda Environments".

NEW QUESTION # 101
Which CLI command allows the customized conda environment to be shared with co-workers?

A. odsc conda modify
B. odsc conda install
C. odsc conda publish
D. odsc conda clone

Answer: C

Explanation:
Detailed Answer in Step-by-Step Solution:
Objective: Share a custom conda environment in OCI Data Science.
Understand Commands: OCI provides odsc CLI for environment management.
Evaluate Options:
A: clone duplicates an environment locally—not for sharing.
B: publish uploads the environment to Object Storage for team access—correct.
C: modify doesn’t exist as a standard command.
D: install sets up an environment locally—not for sharing.
Reasoning: Sharing requires publishing to a shared location (Object Storage), which publish achieves.
Conclusion: B is the correct command.
The OCI Data Science CLI documentation states: “Use odsc conda publish to package and upload a custom conda environment to an Object Storage Bucket, making it accessible to other users.” clone (A) is for local duplication, modify (C) isn’t valid, and install (D) is for local setup—not sharing. B is the designated sharing mechanism.
1: Oracle Cloud Infrastructure Data Science CLI Reference, "odsc conda publish".

NEW QUESTION # 102
You want to write a program that performs document analysis tasks such as extracting text and tables from a document. Which Oracle AI service would you use?

A. OCI Vision
B. Oracle Digital Assistant
C. OCI Language
D. OCI Speech

Answer: A

Explanation:
Detailed Answer in Step-by-Step Solution:
Objective: Select an OCI AI service for text and table extraction from documents.
Evaluate Options:
A: Language—Text analysis, not extraction—incorrect.
B: Digital Assistant—Chatbots, not document tasks—incorrect.
C: Speech—Audio transcription, not documents—incorrect.
D: Vision—OCR for text/tables—correct.
Reasoning: Vision’s OCR extracts text and tables from document images.
Conclusion: D is correct.
OCI documentation states: “OCI Vision (D) uses OCR to extract text and tables from documents, supporting document analysis tasks.” A analyzes text post-extraction, B and C are unrelated—only D fits per OCI’s AI services.
1: Oracle Cloud Infrastructure Vision Documentation, "Document Analysis Features".

NEW QUESTION # 103
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