Data Mining - Classification

Este Curso es parte de

Pathway en Introduction to Data Mining


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.

Asistencia y Certificados

Cuota de Asistencia
GRATUITO!
Costo del Certificado de Participación
GRATUITO!

Categorìa

Informatica, Gestión y Análisis de datos

Horas de Entrenamiento

45

Nivel

Beginner

Metodos de Curso

Tutoría

Idioma

English

Duraciòn

4 Semana

Tipología

Online

Estado del Curso

Tutoría Soft

Iniciar Suscripciones

Apr 4, 2016

Apertura del Curso

Apr 22, 2016

Comenzando la Tutoría

May 2, 2016

Tutoría Final

Jun 30, 2016

Tutoría Soft

Jul 1, 2016

Cierra Curso

No establecido
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.

Basic knowledge of probability, statistics and mathematics.

  • Pang-Ning Tan, Steinbach Michael and Vipin Kumar, (2006). Introduction to Data Mining. Morgan-Kaufmann.
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.

You must accomplish all practice sessions associated with lectures, and then upload, to the course platform, the corresponding KNIME workflow you developed .


FABIO STELLA

FABIO STELLA

Department of Informatics, Systems and Communication