[CAPSTONE] Introduction to Data Mining

Part of the

Pathway in Introduction to Data Mining


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.

Attendance and Credentials

Attendance
FREE!
Attendance Certificate
FREE!

Category

Computer and Data Sciences

Training hours

125

Level

Beginner

Course Mode

Tutored

Language

English

Duration

1 weeks

Type

Online

Course Status

Soft Tutoring

Capstone

Course

Access reserver for the pathway students

Enrollments Start

Mar 31, 2017

Course Opens

May 15, 2017

Tutoring Starts

May 15, 2017

Tutoring Stops

Jun 10, 2017

Soft Tutoring

Jun 11, 2017

Course Closes

Not Set
Basic knowledge of probability, statistics, and mathematics.
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. 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.

FABIO STELLA

FABIO STELLA

Department of Informatics, Systems and Communication

PAOLA CHIESA

PAOLA CHIESA

Department of Informatics, Systems and Communication