Explanation: OCI Jobs can be scheduled or triggered as part of CI/CD pipelines to retrain models periodically, making them essential for automating repeatable operations in MLOps. Which OCI service integrates with Data Science for scalable log ingestion and error monitoring?
C: Incorrect —Git allows simultaneous contributions; it manages, not prevents, merges. D: Incorrect —Centralized is wrong, and “copious data” is vague. Reasoning: Git’s distributed nature (each user has a full repo copy) and change -tracking are core traits. Conclusion: B is accurate. OCI documentation aligns with Git’s official definition: “Git is a distributed version control system that tracks changes to files, enabling collaboration and version history management.” A and D misclassify it as centralized, while C misrepresents merge handling —B captures Git’s essence as used in OCI Data Science. : Oracle Cloud Infrastructure Code Repository Documentation, "Git Overview". Which function's objective is to represent the difference between the predictive value and the target value?
Explanation: A Job Run in OCI can be configured with the desired compute shape and environment variables that are passed into the runtime container for flexible and parameterized executions. Which role does the OCI Model Deployment service play in scaling MLOps operations?
Explanation: A Job Array in OCI lets you run the same job logic multiple times with different parameters (like hyperparameters or datasets), making it useful for hyperparameter tuning or batch scoring tasks. Which feature enables consistent logging of all job runs in OCI Data Science?
Explanation: A standard MLOps workflow breaks the ML lifecycle into modular jobs: ingest, process, train, and evaluate. Each job is versioned and can be rerun, allowing traceable and repeatable pipelines. How can Data Science Jobs be integrated into a CI/CD pipeline? (Choose two)
Explanation: Jobs support reproducibility and automation by decoupling code from interactive sessions. They run in controlled environments and can be scheduled or triggered without manual intervention. What is the primary benefit of enabling autoscaling on an OCI model deployment?
