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Coming SoonIntermediateEst. 8–12 weeks

DataNova Academy Learning Path

Data Engineering

Master the data foundations every serious analytics and AI initiative depends on.

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Coming Soon

This learning experience is currently in development.

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What You'll Learn

  • Enterprise data pipeline design
  • Lakehouse and warehouse patterns
  • Medallion architecture concepts
  • Batch and scalable transformation workflows
  • Data quality and reliability practices
  • Cloud-native data platform fundamentals

Who It's For

  • Aspiring and practicing data engineers
  • Analytics engineers expanding into platforms
  • Professionals supporting AI-ready data estates
  • Teams modernizing legacy data systems

Skills You'll Gain

  • Pipeline engineering
  • Lakehouse design
  • SQL and Python for data workflows
  • Cloud data platform thinking
  • Production data reliability habits

Prerequisites

  • Basic SQL familiarity recommended
  • Willingness to learn cloud data concepts
  • No advanced AI experience required

Expected Learning Outcomes

  • Design scalable data platforms
  • Build trustworthy pipelines
  • Apply medallion and lakehouse patterns
  • Prepare data foundations for analytics and AI

FAQ

Frequently Asked Questions

  • Do I need Python before starting?

    Basic familiarity helps, but the path is designed to strengthen practical Python and SQL skills through applied learning.

  • Is this useful if my company wants AI?

    Yes. DataNova.AI Core believes data comes before AI. Strong data engineering is essential for reliable AI outcomes.

  • When can I enroll?

    Enrollment is not open yet. Join the waiting list to receive updates when this path launches.

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