Introducción al Curso
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.Informatica, Gestión y Análisis de datos
Horas de Entrenamiento45
NivelBeginner
Tutoría
English
Duraciòn4 Semana
TipologíaOnline
Tutoría Soft
Agenda del Curso
Apertura del Curso
Cierra Curso
Resultados de Aprendizaje
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.
Conocimiento Recomendado
Basic knowledge of probability, statistics and mathematics.
Libros de texto y lecturas recomendadas
- Pang-Ning Tan, Steinbach Michael and Vipin Kumar, (2006). Introduction to Data Mining. Morgan-Kaufmann.
Formato del Curso
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.Reglas para la obtención de certificados y Exámenes
Costo del Certificado de Participación
There is no attendance certificate for this course.
