Data Engineering Learning Path

ML Pipeline Engineering

3 concepts · 2 paths · 1 pillar

Progress 0 / 3 complete

Flow

ML Pipeline Engineering

Workflow Orchestration

Data Pipeline Architecture

All Paths

ML Pipeline Engineering → Workflow Orchestration → Data Pipeline Architecture

2 steps

ML Pipeline Engineering → Data Pipeline Architecture

1 step

Concepts in this Path

1 ML Pipeline Engineering

Mark Done Analyze

Data-engineering 5 items Review on Dashboard →

Building Resilient Data Pipelines with Spark and dbt Learn ML Pipeline Orchestration: From Notebook to Production with Feast and MLflow Research Feature Engineering at Scale: Building ML-Ready Market Data Pipelines with dbt and Iceberg Research

2 Workflow Orchestration

Mark Done Evaluate

Data-engineering 3 items Review on Dashboard →

ML Pipeline Orchestration: From Notebook to Production with Feast and MLflow Research Airflow vs Prefect vs Dagster: Choosing the Right Orchestrator in 2026 Research Dagster 2.0: Next-Gen Data Pipeline Orchestration for the Modern Data Platform Research

3 Data Pipeline Architecture

Mark Done Create

Data-engineering 1 items Review on Dashboard →

DataOps: Principles, Practices, and Pipeline Architecture Learn