Data Cleaning Techniques in Data Science & Machine Learning

Course Feature

Cost

Paid
Provider

Udemy
Certificate

Paid Certification
Language

English
Start Date

2020-01-21
Learners

No Information
Duration

No Information
Instructor

Eduonix Learning Solutions

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3.8

168 Ratings

This course provides learners with an in-depth understanding of data cleaning techniques in Data Science & Machine Learning. It covers topics such as data reading, merging or splitting datasets, different visualization tools, locating or handling missing/absurd values, and hands-on sessions. By enrolling in this course, learners will gain the knowledge and skills necessary to effectively clean data for Data Science & Machine Learning. They will also understand why data cleaning is important, and how it can improve decision making, efficiency, and productivity. Learners will have the opportunity to practice their data cleaning skills with a dataset. This course is perfect for new learners who want to gain a comprehensive understanding of data cleaning techniques in Data Science & Machine Learning.

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Course Overview

❗The content presented here is sourced directly from Udemy platform. For comprehensive course details, including enrollment information, simply click on the 'Go to class' link on our website.

Updated in [July 27th, 2023]

This course provides learners with an in-depth understanding of data cleaning techniques in Data Science & Machine Learning. It covers topics such as data reading, merging or splitting datasets, different visualization tools, locating or handling missing/absurd values, and hands-on sessions. Learners will gain an understanding of why data cleaning is important, and how it can improve decision making, efficiency, and productivity. The course also provides learners with the opportunity to practice their data cleaning skills with a dataset. Upon completion of this course, learners will have the knowledge and skills necessary to effectively clean data for Data Science & Machine Learning.

Course Syllabus

Introduction

Playing with the Data

Variables and Correlations

Missing Values and Outliers

Exercises

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