Building Data Pipelines with Python
Building Data Pipelines with Python
.MP4, AVC, 500 kbps, 1280x720 | English, AAC, 128 kbps, 2 Ch | 3.6 hours | 1 GB
Instructor: Katharine Jarmul
.MP4, AVC, 500 kbps, 1280x720 | English, AAC, 128 kbps, 2 Ch | 3.6 hours | 1 GB
Instructor: Katharine Jarmul
This course shows you how to build data pipelines and automate workflows using Python 3. From simple task-based messaging queues to complex frameworks like Luigi and Airflow, the course delivers the essential knowledge you need to develop your own automation solutions. You'll learn the architecture basics, and receive an introduction to a wide variety of the most popular frameworks and tools.
Designed for the working data professional who is new to the world of data pipelines and distributed solutions, the course requires intermediate level Python experience and the ability to manage your own system set-ups.
Acquire a practical understanding of how to approach data pipelining using Python toolsets
Master the ability to determine when a Python framework is appropriate for a project
Understand workflow concepts like directed acyclic graphs, producers, and consumers
Learn to integrate data flows into pipelines, workflows, and task-based automation solutions
Understand how to parallelize data analysis, both locally and in a distributed cluster
Practice writing simple data tests using property-based testing
Building Data Pipelines with Python
