Data Science for Everyone 5-1 Data Cleaning
As a data scientist, you may often encounter datasets that contain many erroneous entries and noises. So, data cleaning is often required to make the dataset be ready for analysis by modifying , imputing, or deleting missing data and noises.
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This course is targeted for managers who are not data scientist but need to manage data analytic projects. This is also targeted for managers who want to introduce data-driven management. So, the knowledge provided in this course is both theoretical and pragmatic, but not includes details of mathematics and coding. However, anyone who are beginners in data science are also welcome because this course can provide you with essentials for learning technical aspects of data science.
Takuma Kimura, Ph.D.
Scientist of Organizational Behavior and Business Analytics
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