Cleaning Data with PySpark

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5

(3)

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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

Working with data can be difficult. It can be frustrating to work with millions or billions of rows. It is possible that you received data processing code from a laptop with very clean data. It is possible that you were responsible for moving basic data processing processes from prototype to production. You might have worked with real-world data. This could include missing fields, unusual formatting or data orders of magnitude larger. Even if you are not an expert on the topic, this course will teach you how to prepare data processes using Python and Apache Spark. This course will help you understand terminology and best practices to create a reliable, manageable and easy-to-understand data processing platform.

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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Intermediate Python

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Introduction to PySpark

What You Will Learn

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Learn how to clean data with Apache Spark in Python

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You’ll learn terminology, methods, and some best practices to create a performant, maintainable, and understandable data processing platform

Course Instructors

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Mike Metzger

Data Engineer Consultant @ Flexible Creations

Mike is a consultant focusing on data engineering and analysis using SQL, Python, and Apache Spark among other technologies. He has a 20+ year history of working with various technologies in the data, networking, and security space.

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