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Data engineering & AI · Corporate training

Databricks & Azure Databricks

Build lakehouse workflows with Python, SQL, Spark, and Delta Lake, including governance and pipeline delivery.

  • Intermediate
  • Live online and in person
  • Duration tailored to your team
Discuss this trainingExplore sample curriculum ↓

Sample curriculum

What your team can learn.

This outline is a starting point. Modules, exercises, and depth are adapted to your team's experience and project requirements.

01Workspace & foundations
  • Workspace, compute, and notebook workflows
  • Python and SQL preparation
  • Lakehouse architecture and data ingestion
02Spark transformations
  • Dataframes and Spark SQL
  • Joins, aggregations, and window functions
  • Partitioning and performance inspection
03Delta Lake & streaming
  • Delta tables, schema handling, and MERGE
  • Incremental ETL and Structured Streaming
  • Declarative pipelines, including Delta Live Tables workflows
04Governance & delivery
  • Unity Catalog and access controls
  • Jobs, orchestration, and data quality
  • CI/CD with Azure DevOps and pipeline review

Hands-on capstone

Put the learning into practice.

Build a bronze-to-gold data pipeline with quality checks, incremental processing, and governed access.

How the training works

Live demonstrations, guided exercises, pair work, and project reviews connect the concepts to practical implementation.

We agree on your learning goals, prerequisites, group size, delivery format, and schedule before shaping the final curriculum and proposal.

Your trainer

I'm Ragav Kumar V, a corporate trainer and mentor with 10+ years of training experience since 2016, 100+ batches delivered, and 3,000+ professionals trained across full-stack development, data engineering, and Cloud & DevOps.

Continue your learning path.