مشروعات تعلم الآلة التطبيقية

Estimated duration: 40 hours (6 modules, 18 lessons + capstone)

What you will learn

• Scope an ML project: business goal, ML framing, success and guardrail metrics, costs of errors and feasibility
• Collect, label and document data with quality checks, consent and licensing
• Choose a validation strategy matching deployment, build baselines and iterate with error analysis
• Run reproducible, tracked experiments with versioned code, data and models
• Deploy models as batch jobs or services and monitor quality, drift and fairness, with retraining plans
• Govern and communicate: model cards, risk reviews, stakeholder reporting and project retrospectives

Who it is for: learners ready to deliver real ML projects for organisations, portfolios or freelance work

Prerequisites: CRS-GEN-SKLEARN (pipelines, model selection); Git basics help