Data Preprocessing with R – Complete Mastery for Practical Use Part 2

Have you been feeling overwhelmed, not knowing where to start with data analysis?

80% of data analysis is preprocessing. No matter how many great analysis techniques you know, you cannot get meaningful results if the data is messy. This course systematically covers essential data preprocessing techniques for practical work from start to finish using R.

This is not a lecture where you simply copy code. We will help you develop true data literacy by understanding why we process data this way and how it is applied in practice.

This is a course consisting only of 'missions' without live sessions or videos.

Data Preprocessing with R – Complete Mastery for Practical Use Part II

In , you will acquire techniques to transform and expand data to fit your analysis.

• Creating new insights through derived variable generation

• Various join methods to combine multiple datasets into one

• Remodeling data structures to fit the purpose of analysis

• From creating summary variables to utilizing GIS coordinate data

Recommended for the following people

• Beginners starting data analysis for the first time

• Those who have learned R but found it difficult to apply in practice

• Job seekers who have struggled with handling missing values and outliers

• Graduate students and researchers who need to clean thesis or research data themselves

• Office workers who feel the limitations of Excel and want to switch to R

Prior knowledge

No prior knowledge is required. However, if you have experience with basic R syntax and reading tabular data, you will be able to follow the course more easily.

To the students,

I sincerely welcome all of you who have chosen to learn despite your busy daily lives. If you have any questions while listening to the lectures, please feel free to leave them at any time. I will be with you until the very end, until the day you can handle data with confidence.