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Pluralsight

Data Cleaning and Processing for Data Scientists

via Pluralsight

Overview

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Data Scientists spend most of their time cleaning and processing their data before they can be leveraged for future predictions. This course will teach you the various data cleaning and processing techniques and how to leverage the cloud services and AI tools to accomplish them.

Properly cleaning and processing the data is crucial to ensure that the subsequent data modeling produces accurate, meaningful, and reliable data. In this course, Data Cleaning and Processing for Data Scientists, you’ll gain the ability to learn the various techniques to pre-process the data that can be used to generate accurate analysis, which will lead to effective decision-making. First, you’ll explore the various data-cleaning techniques and address data with missing values, duplicate data, and outliers. Next, you’ll discover some of the transformation techniques like min-max scaler, standard scaler, one-hot encoding, and dimensionality reduction. Finally, you’ll learn how to leverage the cloud services and AI tools and automate these tasks to achieve results quickly. When you’re finished with this course, you’ll have the skills and knowledge of cleaning and processing the data needed to generate high-quality data for enhanced decision-making.

Syllabus

  • Course Overview 1min
  • Data Cleaning Techniques and Strategies 16mins
  • Data Transformation Techniques and Strategies 16mins

Taught by

Saravanan Dhandapani

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