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Oracle 1z0-1110-25 Exam Syllabus Topics:

Topic	Details
Topic 1	Apply MLOps Practices: This domain targets the skills of Cloud Data Scientists and focuses on applying MLOps within the OCI ecosystem. It covers the architecture of OCI MLOps, managing custom jobs, leveraging autoscaling for deployed models, monitoring, logging, and automating ML workflows using pipelines to ensure scalable and production-ready deployments.
Topic 2	Use Related OCI Services: This final section measures the competence of Machine Learning Engineers in utilizing OCI-integrated services to enhance data science capabilities. It includes creating Spark applications through OCI Data Flow, utilizing the OCI Open Data Service, and integrating other tools to optimize data handling and model execution workflows.
Topic 3	Implement End-to-End Machine Learning Lifecycle: This section evaluates the abilities of Machine Learning Engineers and includes an end-to-end walkthrough of the ML lifecycle within OCI. It involves data acquisition from various sources, data preparation, visualization, profiling, model building with open-source libraries, Oracle AutoML, model evaluation, interpretability with global and local explanations, and deployment using the model catalog.
Topic 4	OCI Data Science - Introduction & Configuration: This section of the exam measures the skills of Machine Learning Engineers and covers foundational concepts of Oracle Cloud Infrastructure (OCI) Data Science. It includes an overview of the platform, its architecture, and the capabilities offered by the Accelerated Data Science (ADS) SDK. It also addresses the initial configuration of tenancy and workspace setup to begin data science operations in OCI.
Topic 5	Create and Manage Projects and Notebook Sessions: This part assesses the skills of Cloud Data Scientists and focuses on setting up and managing projects and notebook sessions within OCI Data Science. It also covers managing Conda environments, integrating OCI Vault for credentials, using Git-based repositories for source code control, and organizing your development environment to support streamlined collaboration and reproducibility.

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Oracle Cloud Infrastructure 2025 Data Science Professional Sample Questions (Q73-Q78):

NEW QUESTION # 73
Which Oracle Cloud Infrastructure (OCI) Data Science policy is invalid?

A. Allow group DataScienceGroup to use virtual-network-family in compartment DataScience
B. Allow dynamic-group DataScienceDynamicGroup to manage data-science-projects in compartment DataScience
C. Allow dynamic-group DataScienceDynamicGroup to manage data-science-family in compartment DataScience
D. Allow group DataScienceGroup to use data-science-model-sessions in compartment DataScience

Answer: D

Explanation:
Detailed Answer in Step-by-Step Solution:
* Objective: Spot the invalid OCI IAM policy.
* Understand Policies: Use verbs (e.g., use, manage) and resource types.
* Evaluate Options:
* A: Valid-virtual-network-family is a resource type.
* B: Invalid-No data-science-model-sessions resource type; likely meant data-science-models.
* C: Valid-data-science-projects is correct.
* D: Valid-data-science-family aggregates Data Science resources.
* Reasoning: B uses a nonexistent resource type-error in syntax.
* Conclusion: B is incorrect.
OCI IAM documentation lists valid resource types: "data-science-models, data-science-projects, data-science- family-but not data-science-model-sessions (B)." A, C, D are correct-B is invalid due to this typo
/misunderstanding.
Oracle Cloud Infrastructure IAM Documentation, "Data Science Resource Types".

NEW QUESTION # 74
You are a data scientist working for a utilities company. You have developed an algorithm that detects anomalies from a utility reader in the grid. The size of the model artifact is about 2 GB, and you are trying to store it in the model catalog. Which THREE interfaces could you use to save the model artifact into the model catalog?

A. Accelerated Data Science (ADS) Software Development Kit (SDK)
B. Git CLI
C. Console
D. OCI Python SDK
E. Oracle Cloud Infrastructure (OCI) Command Line Interface (CLI)
F. ODSC CLI

Answer: A,C,D

Explanation:
Detailed Answer in Step-by-Step Solution:
* Objective: Identify interfaces to save a 2 GB model to the Model Catalog.
* Evaluate Options:
* A: OCI CLI-Supports Data Science tasks-possible but not primary.
* B: ADS SDK-Designed for model catalog ops-correct.
* C: ODSC CLI-Not standard; likely typo for OCI CLI.
* D: Console-GUI for catalog uploads-correct.
* E: OCI Python SDK-Programmatic catalog access-correct.
* F: Git CLI-Version control, not catalog-related.
* Reasoning: B, D, E are OCI's primary interfaces; A is valid but less emphasized.
* Conclusion: B, D, E are correct (A plausible but not top-tier).
OCI documentation lists "ADS SDK (B), OCI Console (D), and OCI Python SDK (E) as primary methods to save models to the Model Catalog." OCI CLI (A) works but isn't highlighted, C isn't real, and F is unrelated- B, D, E are the standard trio.
Oracle Cloud Infrastructure Data Science Documentation, "Model Catalog Interfaces".

NEW QUESTION # 75
You have an image classification model in the model catalog which is deployed as an HTTP endpoint using model deployments. Your tenancy administrator is seeing increased demands and has asked you to increase the load balancing bandwidth from the default of 10Mbps. You are provided with the following information:
* Payload size in KB = 1024
* Estimated requests per second = 120 requests/second (Monday through Friday, in every month, in every year)
* Buffer percentage = 20%What is the optimal load balancing bandwidth to redeploy your model?

A. 452 Mbps
B. 52 Mbps
C. 1152 Mbps
D. 7052 Mbps

Answer: C

Explanation:
Detailed Answer in Step-by-Step Solution:
* Objective: Calculate optimal bandwidth for model deployment.
* Given Data:
* Payload size = 1024 KB = 1024 * 8 = 8192 Kb (kilobits).
* Requests/sec = 120.
* Buffer = 20% = 0.2.
* Calculate Base Bandwidth:
* Bits/sec = Payload * Requests = 8192 Kb * 120 = 983,040 Kb/s = 983.04 Mbps.
* Add Buffer:
* Total = Base * (1 + Buffer) = 983.04 * 1.2 = 1179.648 Mbps.
* Evaluate Options: Closest to 1179.648 Mbps is 1152 Mbps (D)-realistic rounding.
* Conclusion: D is correct.
OCI documentation advises: "Calculate bandwidth as payload size (in bits) * requests/sec, then add a buffer (e.
g., 20%) for peak loads." Here, 1024 KB = 8192 Kb, * 120 = 983.04 Mbps, * 1.2 = 1179.648 Mbps. D (1152 Mbps) is the closest practical option-452 (A) and 52 (B) are too low, 7052 (C) excessive.
Oracle Cloud Infrastructure Data Science Documentation, "Model Deployment - Load Balancing".

NEW QUESTION # 76
Which statement about Oracle Cloud Infrastructure Data Science Jobs is true?

A. You must use a single Shell/Bash or Python artifact to run a job
B. Jobs provisions the infrastructure to run a process on-demand
C. You must create and manage your own Jobs infrastructure
D. Jobs comes with a set of standard tasks that cannot be customized

Answer: B

Explanation:
Detailed Answer in Step-by-Step Solution:
* Objective: Identify a true statement about OCI Data Science Jobs.
* Understand OCI Jobs: Jobs automate ML tasks (e.g., training) on managed infrastructure.
* Evaluate Options:
* A: True-Jobs provision OCI compute resources on-demand for task execution.
* B: False-Users define custom tasks (e.g., Python scripts), not limited to standard ones.
* C: False-Infrastructure is fully managed by OCI, not user-managed.
* D: False-Multiple artifacts (e.g., ZIP with dependencies) can be used, not just one file.
* Reasoning: A reflects OCI's managed, on-demand provisioning model for Jobs.
* Conclusion: A is correct.
The OCI Data Science documentation states: "Jobs provision compute infrastructure on-demand to execute user-defined tasks, such as model training or data processing, on fully managed OCI resources." B is incorrect (customization is allowed), C contradicts the managed nature, and D misstates artifact flexibility-only A accurately describes Jobs.
Oracle Cloud Infrastructure Data Science Documentation, "Jobs Overview".

NEW QUESTION # 77
You are given the task of writing a program that sorts document images by language. Which Oracle service would you use?

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

Answer: A

Explanation:
Detailed Answer in Step-by-Step Solution:
* Objective: Identify the Oracle service to sort document images by language.
* Task Breakdown: Requires extracting text from images (OCR) and detecting language-two potential services involved.
* Evaluate Options:
* A. Oracle Digital Assistant: Builds chatbots-irrelevant to image or language processing.
* B. OCI Language: Detects and classifies languages in text-ideal for sorting after text extraction.
* C. OCI Speech: Transcribes audio to text-not applicable to images.
* D. OCI Vision: Performs OCR to extract text from images-necessary but not sufficient for language sorting.
* Reasoning: The task emphasizes "sorting by language." OCI Vision extracts text, but OCI Language identifies the language (e.g., English, Spanish). Since the question asks for one service and focuses on sorting, OCI Language (B) is the best fit, assuming text extraction is a precursor step.
* Conclusion: B is correct.
OCI Language "provides language detection and classification capabilities, enabling identification of languages in text extracted from documents," per the documentation. OCI Vision handles OCR, but the sorting task aligns with OCI Language (B). Digital Assistant (A) and Speech (C) don't apply, and while Vision (D) is a prerequisite, B is the primary service for language sorting as per OCI's AI service design.
Oracle Cloud Infrastructure Language Documentation, "Language Detection Features".

NEW QUESTION # 78
......

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FREE PDF QUIZ PERFECT ORACLE - 1Z0-1110-25 EXAM OVERVIEW

Free PDF Quiz Perfect Oracle - 1z0-1110-25 Exam Overview