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Oracle 1Z0-1110-26 Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: MLOps and OCI Integration	20%	- OCI ecosystem 1. IAM and security 2. Object Storage - Automation and pipelines 1. CI/CD integration 2. Model lifecycle management
Topic 2: Model Development and Deployment	30%	- Model deployment 1. Prediction endpoints 2. Deployment creation - Model training 1. Experiments 2. Hyperparameter optimization
Topic 3: Machine Learning Fundamentals	20%	- Supervised learning 1. Classification 2. Regression - Unsupervised learning 1. Clustering 2. Dimensionality reduction
Topic 4: OCI Data Science Service	30%	- Model catalog 1. Model metadata 2. Model versioning - Projects and notebooks 1. Notebook sessions 2. Conda environments

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Oracle Cloud Infrastructure Data Science Professional Sample Questions (Q132-Q137):

NEW QUESTION # 132
As a data scientist, you are tasked with creating a model training job that is expected to take different hyperparameter values on every run. What is the most efficient way to set those parameters with Oracle Data Science Jobs?

A. Create a new job every time you need to run your code and pass the parameters as environment variables
B. Create a new job by setting the required parameters in your code, and create a new job for every code change
C. Create your code to expect different parameters as command-line arguments, and create a new job every time you run the code
D. Create your code to expect different parameters either as environment variables or as command-line arguments, which are set on every job run with different values

Answer: D

Explanation:
Detailed Answer in Step-by-Step Solution:
Objective: Efficiently manage varying hyperparameters in OCI Data Science Jobs.
Understand OCI Jobs: Jobs execute predefined tasks with configurable inputs (e.g., env vars, args).
Evaluate Options:
A: New job per run with env vars—Redundant job creation, inefficient.
B: New job per run with args—Similarly inefficient due to repeated setup.
C: Hardcode params, new job per change—Highly inefficient, requires code edits.
D: Single job, flexible params via env vars or args—Efficient, reusable—correct.
Reasoning: D minimizes job creation, allows runtime flexibility via configuration—best practice.
Conclusion: D is correct.
OCI documentation states: “For Jobs with varying hyperparameters, write code to accept environment variables or command-line arguments (D), then configure these per Job Run using the OCI Console or SDK—most efficient approach.” Options A, B, and C involve unnecessary job proliferation or code changes—only D aligns with OCI’s design for parameterized runs.
1: Oracle Cloud Infrastructure Data Science Documentation, "Configuring Job Runs with Parameters".

NEW QUESTION # 133
As a data scientist, you use the Oracle Cloud Infrastructure (OCI) Language service to train custommodels. Which types of custom models can be trained?

A. Sentiment Analysis, Named Entity Recognition (NER)
B. Object detection, Text classification
C. Image classification, Named Entity Recognition (NER)
D. Text classification, Named Entity Recognition (NER)

Answer: D

Explanation:
Detailed Answer in Step-by-Step Solution:
Objective: Identify custom model types for OCI Language service.
Understand OCI Language: Focuses on text analysis, not images.
Evaluate Options:
A: Image classification—Incorrect; Language is text-based.
B: Text classification, NER—Both text tasks—correct.
C: Sentiment—Pretrained, not custom; NER ok—incorrect.
D: Object detection—Image-based, incorrect.
Reasoning: B aligns with OCI Language’s custom text capabilities.
Conclusion: B is correct.
OCI documentation states: “OCI Language supports training custom models for text classification and Named Entity Recognition (NER) (B) using user data.” A and D involve images, C includes pretrained sentiment—only B matches OCI Language’s custom model scope.
1: Oracle Cloud Infrastructure Language Documentation, "Custom Model Types".

NEW QUESTION # 134
You realize that your model deployment is about to reach its utilization limit. What would you do to avoid the issue before requests start to fail? Pick THREE.

A. Update the deployment to use fewer instances
B. Reduce the load balancer bandwidth limit so that fewer requests come in
C. Delete the deployment
D. Update the deployment to use a larger virtual machine (more CPUs/memory)
E. Update the deployment to add more instances

Answer: B,D,E

Explanation:
Detailed Answer in Step-by-Step Solution:
Objective: Prevent deployment failure due to high utilization.
Evaluate Options:
A: More instances—Scales capacity—correct.
B: Delete—Stops service, not a solution.
C: Fewer instances—Worsens utilization.
D: Larger VM—Increases resource capacity—correct.
E: Reduce bandwidth—Limits load—correct.
Reasoning: A and D boost capacity, E controls demand—proactive fixes.
Conclusion: A, D, E are correct.
OCI documentation advises: “To handle high utilization, increase instances (A), use a larger compute shape (D), or adjust load balancer bandwidth (E) to manage request volume.” B stops service, C reduces capacity—only A, D, E prevent failure per OCI’s scaling options.
1: Oracle Cloud Infrastructure Data Science Documentation, "Model Deployment Scaling".

NEW QUESTION # 135
Which type of firewalls are designed to protect against web application attacks, such as SQL injection and cross-site scripting?

A. Stateful inspection firewall
B. Web Application Firewall
C. Packet filtering firewall
D. Incident firewall

Answer: B

Explanation:
Detailed Answer in Step-by-Step Solution:
Objective: Identify the firewall type protecting against web app attacks like SQL injection and XSS.
Understand Firewall Types:
Stateful Inspection: Tracks connection states, not app-specific.
Web Application Firewall (WAF): Targets web app vulnerabilities.
Incident Firewall: Not a recognized term.
Packet Filtering: Basic packet rules, not app-aware.
Evaluate Options:
A: Stateful—General network, not web-specific—incorrect.
B: WAF—Designed for SQLi, XSS—correct.
C: Incident—Non-existent—incorrect.
D: Packet—Low-level, not app-focused—incorrect.
Reasoning: WAF specializes in web app security—matches requirement.
Conclusion: B is correct.
OCI documentation states: “Web Application Firewall (WAF) (B) protects against web application attacks like SQL injection and cross-site scripting by inspecting HTTP traffic.” A and D handle network-level threats, C isn’t real—only B aligns with OCI’s WAF purpose.
1: Oracle Cloud Infrastructure WAF Documentation, "Overview".

NEW QUESTION # 136
How can you convert a fixed load balancer to a flexible load balancer?

A. Use Update Shape workflows
B. Using the Edit Listener option
C. Delete the fixed load balancer and create a new one
D. There is no way to convert the load balancer

Answer: C

Explanation:
Detailed Answer in Step-by-Step Solution:
Objective: Convert fixed to flexible load balancer in OCI.
Understand Load Balancers: Fixed (e.g., 10 Mbps) vs. flexible (dynamic shapes).
Evaluate Options:
A: False—Conversion possible via recreation.
B: Update Shape—For flexible only, not conversion.
C: Delete and recreate—Standard method—correct.
D: Edit Listener—Configures rules, not type.
Reasoning: OCI requires new creation for type change.
Conclusion: C is correct.
OCI documentation states: “To change from a fixed to a flexible load balancer, delete the existing fixed load balancer and create a new flexible one (C)—direct conversion isn’t supported.” A is too absolute, B and D don’t apply—only C matches OCI’s process.
1: Oracle Cloud Infrastructure Load Balancing Documentation, "Changing Load Balancer Type".

NEW QUESTION # 137
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