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| Section | Weight | Objectives |
|---|---|---|
| Apply MLOps Practices | 20% | - Model monitoring, drift detection, and performance tracking - ML pipelines, automation, and reproducibility - Governance, auditing, and compliance |
| Integrate Related OCI Services | 10% | - Integration with OCI Object Storage, Vault, and Networking - Use OCI AI and data services with Data Science |
| Design and Set Up Data Science Workspace | 15% | - Create and manage projects and notebook sessions - Configure compute shapes, storage, and networking - Manage access control, security, and IAM integration |
| Implement End-to-End Machine Learning Lifecycle | 45% | - Deploy models and manage endpoints - Use AutoML and built-in algorithms - Model saving, cataloging, and versioning - Data preparation, exploration, and transformation - Model development, training, and evaluation |
| OCI Data Science - Introduction & Configuration | 10% | - Capabilities of the Accelerated Data Science (ADS) SDK - Tenancy and environment configuration for Data Science - Overview and core concepts of OCI Data Science |
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NEW QUESTION # 48
You loaded data into Oracle Cloud Infrastructure (OCI) Data Science. To transform the data, you want to use the Accelerated Data Science (ADS) SDK. When you applied the get_recommendations() tool to the ADSDataset object, it showed you user-detected issues with all the recommended changes to apply to the dataset. Which option should you use to apply all the recommended transformations at once?
Answer: C
Explanation:
Detailed Answer in Step-by-Step Solution:
Objective: Apply all recommended transformations from get_recommendations() in ADS.
Understand ADS Tools: get_recommendations() suggests fixes (e.g., missing values).
Evaluate Options:
A: Returns transformed data—Not for applying—incorrect.
B: Sklearn-style, not ADS-specific—incorrect.
C: auto_transform()—Applies all recommendations—correct.
D: Visualizes, doesn’t apply—incorrect.
Reasoning: auto_transform() executes the fixes suggested by get_recommendations().
Conclusion: C is correct.
OCI documentation states: “After get_recommendations() identifies issues, use auto_transform() (C) on the ADSDataset to apply all recommended transformations at once.” A retrieves, B is external, D visualizes—only C aligns with OCI’s ADS transformation workflow.
1: Oracle Cloud Infrastructure ADS SDK Documentation, "Data Transformation Methods".
NEW QUESTION # 49
Which stage in the machine learning life cycle helps in identifying the imbalance present in the data?
Answer: D
Explanation:
Detailed Answer in Step-by-Step Solution:
Objective: Find the stage where data imbalance (e.g., skewed classes) is identified.
Understand Stages:
Data Modeling: Training models—assumes data is prepared.
Data Monitoring: Post-deployment tracking—not for initial analysis.
Data Exploration: Analyzing data properties (e.g., distributions)—key for imbalance.
Data Access: Retrieving data—no analysis yet.
Evaluate Options:
A: Modeling uses data, doesn’t detect imbalance—incorrect.
B: Monitoring tracks performance, not initial data issues—incorrect.
C: Exploration (e.g., via pandas) reveals imbalances—correct.
D: Access is just retrieval—incorrect.
Reasoning: Imbalance is assessed during exploration (e.g., class counts).
Conclusion: C is correct.
OCI documentation notes: “Data Exploration involves analyzing the dataset to understand its characteristics, such as identifying class imbalances or missing values, using tools like ADS SDK or Jupyter notebooks.” Modeling (A) and Monitoring (B) occur later, while Access (D) is pre-analysis—only Exploration (C) fits this role.
1: Oracle Cloud Infrastructure Data Science Documentation, "Data Exploration Stage".
NEW QUESTION # 50
Arrange the following in the correct Git Repository workflow order:
Install, configure, and authenticate Git.
Configure SSH keys for the Git repository.
Create a local and remote Git repository.
Commit files to the local Git repository.
Push the commit to the remote Git repository.
Answer: B
Explanation:
Detailed Answer in Step-by-Step Solution:
Step 1: Install, configure, and authenticate Git: Git must be installed and configured (e.g., git config --global user.name) before any repository actions.
Step 2: Configure SSH keys: SSH keys are set up (e.g., ssh-keygen) and added to the remote service (e.g., GitHub, OCI Code Repository) for secure access.
Step 3: Create local and remote Git repository: Initialize a local repo (git init) and create/link a remote repo (e.g., git remote add origin).
Step 4: Commit files: Add files (git add .) and commit them locally (git commit -m "message").
Step 5: Push to remote: Push local commits to the remote repo (git push origin main).
Evaluate Options: Only D (1, 2, 3, 4, 5) follows this logical sequence; others (e.g., A starts with SSH before Git installation) are illogical.
The standard Git workflow in OCI Data Science or general practice begins with installing Git (1), configuring SSH for secure access (2), creating repositories (3), committing locally (4), and pushing remotely (5). The OCI Code Repository documentation aligns with this: “First, install Git and configure authentication (e.g., SSH), then set up repositories and manage code.” D is the only option reflecting this industry-standard process.
1: Oracle Cloud Infrastructure Code Repository Documentation, "Git Workflow Basics".
NEW QUESTION # 51
You want to create a user group for a team of external data science consultants. The consultants should only have the ability to see Data Science resource details but not have the ability to create, delete, or update Data Science resources. What verb should you write in the policy?
Answer: A
Explanation:
Detailed Answer in Step-by-Step Solution:
Understand OCI IAM Policies: Policies control access using verbs like “inspect,” “read,” “use,” and “manage.” Define Requirement: Consultants need view-only access without modification rights.
Evaluate Verbs:
A . Use: Allows interaction (e.g., running jobs)—too permissive.
B . Inspect: Grants view-only access to resource details—matches requirement.
C . Manage: Full control (create, update, delete)—too permissive.
D . Read: Includes viewing content (e.g., data), not just metadata—slightly broader than needed.
Conclusion: “Inspect” (B) is the precise verb for view-only access to resource details.
In OCI Identity and Access Management (IAM), the “inspect” verb allows listing and viewing resource metadata without granting modification or data access rights, ideal for this scenario. This is confirmed in the IAM policy reference. (Oracle Cloud Infrastructure Documentation, "IAM Policy Verbs").
NEW QUESTION # 52
You are a data scientist leveraging the Oracle Cloud Infrastructure (OCI) Language AI service for various types of text analyses. Which TWO capabilities can you utilize with this tool?
Answer: B,D
Explanation:
Detailed Answer in Step-by-Step Solution:
Objective: Identify two OCI Language AI capabilities.
Understand OCI Language: Focuses on text analysis tasks.
Evaluate Options:
A: Table extraction—Vision, not Language—incorrect.
B: Punctuation correction—Not offered—incorrect.
C: Sentence diagramming—Not supported—incorrect.
D: Topic classification—Supported (custom/pretrained)—correct.
E: Sentiment analysis—Supported (pretrained)—correct.
Reasoning: D and E are core text analysis features of OCI Language.
Conclusion: D and E are correct.
OCI documentation states: “OCI Language offers topic classification (D) and sentiment analysis (E) for text analysis, among other features.” A belongs to Vision, B and C aren’t available—only D and E match OCI Language’s capabilities.
1: Oracle Cloud Infrastructure Language Documentation, "Text Analysis Features".
NEW QUESTION # 53
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