Oracle Cloud Infrastructure Data Science Professional: Hands-On Workshop

Course Description

Oracle Cloud Infrastructure Data Science Professional: Hands-On Workshop develops practical capability in building and operating OCI Data Science solutions through projects, notebook sessions, ADS, feature preparation, model training, deployment, and MLOps. The learning path is organized around a customer-churn model developed in OCI Data Science and promoted through a controlled deployment.

Learners progress from product architecture and workflow understanding into configuration, development, analysis, validation, troubleshooting, and operational handoff. Every lesson uses the controls, tools, data structures, risks, failure modes, and decisions relevant to this exact Oracle pathway.

The content is independently written for SkillDynamo using the supplied source page for title, update date, and topic alignment. Learners finish with reproducible evidence, a course-specific implementation record or runbook, and a prioritized improvement action.

What You Will Learn

• Explain and apply projects, notebook-session shapes, block volumes, networking, and lifecycle within Oracle Cloud Infrastructure Data Science Professional: Hands-On Workshop.
• Configure, validate, or troubleshoot conda environments, package management, Git, storage, and reproducibility, ADS data access, OCI authentication, resource principals, and policies, and workspaces, naming, ownership, cost controls, and environment validation using course-specific evidence.
• Explain and apply Object Storage, Autonomous Database, file, and dataset connectivity within Oracle Cloud Infrastructure Data Science Professional: Hands-On Workshop.
• Configure, validate, or troubleshoot profiling, missing values, outliers, leakage, sampling, and splits, ADS transformations, categorical encoding, scaling, and feature selection, and versioned datasets, lineage, quality evidence, and repeatable preparation using course-specific evidence.
• Explain and apply classification, regression, forecasting, and algorithm selection within Oracle Cloud Infrastructure Data Science Professional: Hands-On Workshop.
• Configure, validate, or troubleshoot metrics, cross-validation, imbalance, thresholds, and error analysis, hyperparameter tuning, AutoML awareness, experiments, and comparison, and explainability, bias review, model catalog metadata, and approvals using course-specific evidence.
• Explain and apply model artifacts, runtime environments, deployments, endpoints, and scaling within Oracle Cloud Infrastructure Data Science Professional: Hands-On Workshop.
• Configure, validate, or troubleshoot request schemas, batch versus online inference, testing, and rollback, logs, metrics, latency, drift indicators, failures, and alarms, and pipelines, retraining, governance, documentation, and model runbook using course-specific evidence.

SkillDynamo Training Approach

The training follows a customer-churn model developed in OCI Data Science and promoted through a controlled deployment. Activities combine product-specific demonstrations, guided implementation, hands-on exercises, scenario analysis, validation checklists, structured troubleshooting, solution review, and a final improvement plan. Learners document assumptions, settings, commands or transactions, outputs, exceptions, corrective actions, security and governance trade-offs, rollback needs, and operational ownership.