Parallel Programming with Dask in Python

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Learn to upscale your Python workflows to efficiently handle big data with Dask.
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When working with big data, you’ll face two common obstacles: using too much memory and long runtimes. The Dask library can lower your memory use by loading chunks of data only when needed. It can lower runtimes by using all your available computing cores in parallel. Best of all, it requires very few changes to your existing Python code. In this course, you use Dask to analyze Spotify song data, process images of sign language gestures, calculate trends in weather data, analyze audio recordings, and train machine learning models on big data.

Instructor(s)

James Fulton
DataCamp
via DataCamp
Free Trial Available
English
4 Hours
Self paced