Oracle Cloud Infrastructure Data Science Professional (2023): Hands-On Workshop

Course Description

Oracle Cloud Infrastructure Data Science Professional (2023): Hands-On Workshop develops practical capability in oci data science projects, notebook sessions, conda environments, storage, and iam and ads data connections, data preparation, transformation, feature selection, and quality. The course connects Oracle architecture, configuration, development, or functional processing to business ownership, security, data quality, control requirements, and measurable acceptance criteria.

Learners then work through model development, automl awareness, evaluation, explainability, and model catalog and jobs, deployments, endpoints, pipelines, logs, monitoring, and operational handover. Each activity produces notebook and environment settings, data-connection tests, preparation outputs, model comparisons, evaluation metrics, catalog records, job runs, endpoint responses, and logs, helping participants separate configuration defects from data, access, integration, performance, or operational failures.

By completing the learning path, participants can support a 2023 OCI Data Science workflow used to prepare data, compare models, register an approved artifact, and deploy a controlled prediction endpoint. They also create a practical improvement plan covering validation, exception handling, rollback, ownership, documentation, monitoring, and production support.

What You Will Learn

• Assess oci data science projects, notebook sessions, conda environments, storage, and iam within a controlled Oracle Cloud Infrastructure Data Science Professional (2023): Hands-On Workshop workflow.
• Verify risks involving environment drift, failed authentication, bad splits, overfitting, misleading metrics, unapproved artifacts, endpoint errors, and missing operational ownership while producing defensible implementation evidence.
• Model ads data connections, data preparation, transformation, feature selection, and quality within a controlled Oracle Cloud Infrastructure Data Science Professional (2023): Hands-On Workshop workflow.
• Analyze risks involving environment drift, failed authentication, bad splits, overfitting, misleading metrics, unapproved artifacts, endpoint errors, and missing operational ownership while producing defensible implementation evidence.
• Implement model development, automl awareness, evaluation, explainability, and model catalog within a controlled Oracle Cloud Infrastructure Data Science Professional (2023): Hands-On Workshop workflow.
• Document risks involving environment drift, failed authentication, bad splits, overfitting, misleading metrics, unapproved artifacts, endpoint errors, and missing operational ownership while producing defensible implementation evidence.
• Control jobs, deployments, endpoints, pipelines, logs, monitoring, and operational handover within a controlled Oracle Cloud Infrastructure Data Science Professional (2023): Hands-On Workshop workflow.
• Operationalize risks involving environment drift, failed authentication, bad splits, overfitting, misleading metrics, unapproved artifacts, endpoint errors, and missing operational ownership while producing defensible implementation evidence.

SkillDynamo Training Approach

Delivery combines Oracle-specific demonstrations, guided hands-on exercises, scenario analysis, validation checklists, structured troubleshooting, solution review, and a final improvement plan. Learners document assumptions, settings, data, outputs, exceptions, corrective actions, rollback needs, approvals, evidence, and operational responsibilities.