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Data Engineering for ML (ETL, Quality, Features)

Build reliable datasets for ML: validation, feature-ready tables, and training/serving parity foundations.

Data EngineeringETLData QualityFeatures

Duration

3 days

Format

Remote

Level

Intermediate

Key outcomes

  • Design datasets for training/inference parity
  • Implement validation and quality checks
  • Structure features and transformations for reuse
  • Avoid common pipeline failure modes

Program

Detailed syllabus will be published soon. Contact us to receive the latest version.