Outlier Detection Techniques

Welcome to the course "Outlier Detection Techniques". This course is the first course of its kind. You might try to look for courses in this subject, and you will surprised to discover that you will hardly find any courses, despite the importance and huge academic publications on the issue. So, this course  "Outlier Detection Techniques" is unique.
Outlier detection is a primary step in many data mining applications, data analysis and researches. In this course, you will learn approaches that come from Statistics discipline and Data Mining. You will learn four algorithms for detection outliers in Univariate space, two algorithms in multivariate space and also learn innovative algorithm for detection outliers in high-dimensional space.

You will be impress, that  "Outlier Detection Techniques" it is a world unto itself. It is a complex but very interesting world.
The course is suitable for everyone, even if you have no background in statistics and linear algebra. The most important thing is desire to learn.
I am convinced that only those who are familiar with the details of the methodology and know all the stages of the calculation, can understand it in depth. So, in my teaching method, I put a stronger emphasis on understanding the material, and less on programming. However, anyone who interested in programming, I developed all algorithms in R,  so you can download and run them.
At the end of the course, you will not only be familiar with a variety of "Outlier Detection Techniques", but also know to implement them. During the course, i put a strong emphasis on practice(including quizzes) to make sure you understand the topics.
I sincerely hope you will enjoy the course.
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