Basic statistical knowledge.
Robust data analysis and outlier detection are crucial in Statistics, Data Analysis, Data Mining, Machine Learning, Pattern Recognition, Artificial Intelligence, Classification, Principal Components, Regression, Big Data, and any field related with data.
Researchers, students, data analyst, and mostly anyone who is dealing with real data have to be aware of the problem with outliers and they have to know how to deal with this issue.
The implementation and example codes are available in the open Google Drive repository.
In addition, we have two sections of basic concepts that will help you to remember some notions necessary to understand the methods for outlier detection.
With this course you will master one of the most important issues today both academically, as in industry and in data analysis. The examples will help you to visualize this importance and as a guide to carry out these analyzes by yourself.
Who this course is for: