Introduction to Data Mining

Titolo di Studio: Laurea Triennale

Lingua: English

Categoria: Computer and Data Sciences

Durata: 245 Ore

Frequenza: Gratuito

665 Studenti Iscritti

11 Set

2016

Non impostato

Sommario

The Introduction to Data Mining pathway teaches you how to use the data mining methodology to analyze both structured, semi-structured and un-structured data. The pathway consists of the following courses; Classification, Clustering and Association, and Text Mining. You will learn how to develop data mining workflows using the KNIME open source software platform. You are not required to code any programs while KNIME allows you to use open source programming languages and powerful commercial software environments; R, Weka, Matlab, Python, Java, ... and to access data from powerful platforms such as Twitter and Google.
Pre-requisiti

Basic knowledge of probability, statistics, and mathematics.
Course sequence

You should attend the three courses of the Pathway in the following order: Classification, Clustering and Association, and Text Mining. However, if you know how to use the KNIME open source platform, have basic knowledge of the R programming language, then, no special order applies.
Evaluation and Certificates

Each course of the Pathway issues an Attendance Certificate and a Badge whether the following conditions are fulfilled: all practice sessions associated with each lecture are accomplished; the KNIME workflow associated with each practice session is uploaded to the course platform.
Box3 Title

Box3 Text
Box4 Title

Box4 Text
Docenti e Tutor

FABIO STELLA

Department of Informatics, Systems and Communication