Details
Duration (weeks):
4
Workload (hrs/week):
45
Language:
English
EduOpen
Home Page:
Homepage
About:
Learn how to formulate and solve classification problems for use in Data Mining and Business Intelligence applications such as; fraud detection, customer churning, network intrusion detection, etc... You will learn how to develop, validate and apply a data mining workflow to solve binary and non-binary classification problems. The course is self-contained, and it does not require any programming skills. Hands-on lectures are based on the KNIME open source software platform.
Aim:
By the end of this course, you will be able to:
- develop a Data Mining workflow for solving a classification problem,
- apply elementary missing replacement strategies,
- apply pre-processing techniques including dimensionality reduction,
- select and deploy the “optimal classifier” (whatever it means) also taking into account decision costs,
- select relevant attributes and remove not relevant and/or redundant attributes.
You will learn all this using the KNIME open source platform, which integrates power and expressiveness of Weka, R and Java.
Syllabus:
The course spans four weeks. Each week requires 8 to 10 hours of work. Each week consists of 5 to 7 video-lectures. Each video-lecture consists of a methodology video, a software usage video and a practice session.
Entry Requirements:
Basic knowledge of probability, statistics and mathematics.
