Principles of Data Cleaning

Learn how to clean data the right way.

Instructed by Phikolomzi Gugwana

  • You will IMMEDIATELY be able to apply these data cleaning principles to your work, across all data science tools.

In this course, you will learn the fundamental principles of Data Cleaning. This course comprises of 5 separate examples, and in each example, we clean a different data set. You will learn how to handle missing values, skewed variables and how to clean data to suit a specific analytical requirement. 

  • Microsoft Excel
  • Data Scientists
  • Data Analysts
  • Statisticians
  • Anyone who is curious about data and is eager to learn
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Section 1 : Course Material

  • Lecture 1 :

Section 2 : Introduction

  • Lecture 1 :
  • What is data cleaning?
  • Lecture 2 :
  • Determinants of data cleaning
  • Lecture 3 :
  • Data Integrity
  • Lecture 4 :
  • The Solution
  • Lecture 5 :
  • The Variable

Section 3 : Example 1

  • Lecture 1 :
  • Example 1
  • Lecture 2 :
  • Example 1 Demo
  • Lecture 3 :
  • Quiz 1
  • Quiz 1

Section 4 : Example 2

  • Lecture 1 :
  • Example 2
  • Lecture 2 :
  • Example 2 Demo
  • Lecture 3 :
  • Quiz 2
  • Quiz 2

Section 5 : Example 3

  • Lecture 1 :
  • Example 3
  • Lecture 2 :
  • Example 3 Demo
  • Lecture 3 :
  • Quiz 3
  • Quiz 3

Section 6 : Example 4

  • Lecture 1 :
  • Example 4
  • Lecture 2 :
  • Example 4 Breakdown
  • Lecture 3 :
  • Example 4 Demo
  • Lecture 4 :
  • Quiz 4
  • Quiz 4

Section 7 : Example 5

  • Lecture 1 :
  • Example 5
  • Lecture 2 :
  • Example 5 Lecture 2
  • Lecture 3 :
  • Example 5 Lecture 3
  • Lecture 4 :
  • Example 5 Demo
  • Lecture 5 :
  • Quiz 5
  • Quiz 5

Section 8 : Conclusion

  • Lecture 1 :
  • Conclusion

Phikolomzi Gugwana,

I am a Data Scientist with a background in Statistics and Economics. I have experience in the oil and gas industry. I have a passion for learning and teaching. I believe that the solutions to the world's problems will come if we share knowledge and work together.
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