Excel Data Cleaning Fundamentals

Course Feature

Cost

Paid
Provider

Udemy
Certificate

Paid Certification
Language

English
Start Date

2022-09-25
Learners

No Information
Duration

No Information
Instructor

Nasiru Musa

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3.9

105 Ratings

This Excel Data Cleaning Fundamentals course is perfect for new learners who want to learn how to detect and fix errors in datasets imported into Excel for analysis. It provides step-by-step instructions, follow-along exercises, case study exercises, and quizzes to teach learners how to use basic to advanced Excel functions, concepts, and techniques in a fast and efficient way. No need for macros or any Excel add-on tools - the techniques taught in this course are simple yet effective. Click now to start learning and become an Excel data cleaning expert!

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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 Excel Data Cleaning Fundamentals course provides learners with the skills needed to identify and correct errors that occur when datasets are imported into Excel for analysis. Step-by-step instructions, exercises, case studies, and quizzes are used to teach learners how to use basic to advanced Excel functions, concepts, and techniques quickly and efficiently. No macros or Excel add-on tools are required to use the techniques taught in this course.

Course Syllabus

Introduction Data Cleaning

Data Cleaning- Text Values

Text Values Data Cleaning: First Name Column Values

Text Values Data Cleaning Exercise: Last Name Column Values

Text Values Data Cleaning Exercise: Address Column Values

Text Values Data Cleaning Exercise: Passport Column Values

Text Values Data Cleaning Exercise: Mobile Phone Column Values

Text Values Data Cleaning Exercise: Currency Column Values

Text Values Data Cleaning Exercise: Country Column Values

Text Values Data Cleaning Exercise: Airport Column Values

Date Values: Data Cleaning Exercise

Number Data Values: Data Cleaning Exercise

Removing Duplicate Records

Data Normalization

Practice Exercises: Sample Dataset

Review and Conclusion

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