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Parallel Programming with Dask in Python

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$12

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Course Features

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Duration

4 hours

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Delivery Method

Online

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Available on

Limited Access

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Accessibility

Mobile, Desktop, Laptop

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Language

English

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Subtitles

English

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Level

Intermediate

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Teaching Type

Self Paced

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Video Content

4 hours

Course Description

Python is well-known for its ability to perform data analysis and data science. Data scientists consider the greatest limitation of Python to be the requirement that all data must fit into the available memory. Python can only run on one CPU. Data scientists ask, "How can I read and process large amounts of data?" How can I make the most of my computational processing resources? This course will introduce Dask, an Open-Source Parallel Computing Library that allows for analytical computing. With Dask, you can scale up your Python workflows to large datasets directly from your computer.

Course Overview

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Virtual Labs

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International Faculty

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Post Course Interactions

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Hands-On Training,Instructor-Moderated Discussions

Skills You Will Gain

Prerequisites/Requirements

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Data Manipulation with pandas

What You Will Learn

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Learn to upscale your Python workflows to efficiently handle big data with Dask

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You’ll face two common obstacles: using too much memory and long runtimes

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You'll learn the difference between these two task scheduling methods and which one is better under which circumstances

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You'll learn how everything you know about NumPy and pandas can easily be applied to data that is too large to fit in memory

Course Instructors

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Team Anaconda

Data Science Training

This course was created in collaboration with Anaconda. With over 6 million users, the open source Anaconda Distribution is the fastest and easiest way to do Python data science and machine learning....

Course Reviews

Average Rating Based on 3 reviews

5.0

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Course Cover

$12

$6

49% OFF

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