ML Data Engineer Roadmap

Complete path to become a Machine Learning Data Engineer

Overview

This roadmap guides you through becoming a Machine Learning Data Engineer. You'll learn data pipelines, ML infrastructure, and production systems.

Duration: 12-18 months
Progress: 25%

Foundation (3-4 months)

40%

Python Basics

Master Python fundamentals, data types, functions, and OOP

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SQL & Databases

Learn SQL, database design, and data modeling

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Data Structures & Algorithms

Essential algorithms for data processing

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Intermediate (4-6 months)

10%

Data Pipelines

Build ETL pipelines with Apache Airflow

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Big Data Tools

Apache Spark, Hadoop, and distributed computing

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Advanced (5-8 months)

0%

ML Infrastructure

MLOps, model deployment, and production systems

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Cloud Platforms

AWS, GCP, Azure for ML and data engineering

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