Lakehouse AI enablement for engineering teams
Practical courses for teams building Delta Lake, Spark, Unity Catalog, MLflow, and Mosaic AI workflows.
Maya Chen
Senior ML Platform Engineer
Active courses
4
Three courses and one certificate are in progress.
Completion
58%
Demo progress is seeded and updates locally.
Team rank
#4
Based on the mocked leaderboard.
Featured curriculum
A compact sales-demo catalog, backed by the Databricks bundle.
Delta Lake Table Design for Reliable AI Data
Design Delta tables with transaction guarantees, schema controls, history, and file layout that support batch and streaming workloads.
Lakeflow and Structured Streaming Pipelines
Build incremental ingestion pipelines with Auto Loader concepts, streaming tables, expectations, and operational handoffs.
Spark Performance for Data Teams
Tune Spark SQL and DataFrame workloads by reading plans, choosing partitions, and avoiding shuffle-heavy surprises.
Lakehouse Data Engineer
Build reliable Delta Lake pipelines with ingestion, quality, streaming, and Spark performance practices.
Open path
Governed AI Platform Engineer
Connect Unity Catalog, MLflow, model serving, evaluation, and release controls for enterprise AI systems.
Open path
Lakehouse AI Readiness
A compact readiness path for technical leaders aligning data, model, and governance practices.
Open path