PATH

Data Engineer

Learn how to build data pipelines to work with large data sets.

This path teach you how to utilize Python along with pandas to work with large data sets and loading them into a Postgres database. In this path, you'll learn how to work with big data, building data pipelines, and more.

Throughout this path, you will learn the following

  • How to work with production databases
  • Key computer science concepts like data structures, algorithms, and recursion.
  • How to handle larger data sets.

START LEARNING

60+ FREE MISSIONS

By creating an account you agree to accept our terms of use and privacy policy.

Become a Data Engineer

Postgres for Data Engineers

Learn about the SQL database Postgres.

Optimizing Postgres Databases

Learn how to optimize your Postgres databases.

Processing Large Datasets in Pandas

Learn how to work with datasets by optimizing your pandas workflow, processing data in batches, and augmenting pandas with SQLite.

Optimizing Code Performance on Large Datasets

Learn how to process data more quickly by optimizing CPU and I/O performance. Learn to parallelize your code for better performance.

Algorithms & Data Structures

Learn about different data structures, and how they can help speed up your data analysis.

Recursion & Trees

Learn about recursion and how it applies to tree data structures, and how tree data structures are used to speed up processing of data analysis tasks.

Building a Data Pipeline

Learn how to build a Python data pipeline from scratch.