Hands On Training

Data Mining with Weka

via

Future Learn

Course Features

Duration

5 weeks

Delivery Method

Online

Available on

Lifetime Access

Accessibility

Mobile, Desktop

Language

English

Subtitles

English

Level

Intermediate

Effort

3 hours per week

Teaching Type

Self Paced

Course Description

The world of today generates more data than ever! It is essential to be able turn this data into useful information. This course will teach you how to use the Weka workbench to do data mining. The mystery surrounding this subject will be dispelled. We will explain the basic principles behind popular algorithms. You'll learn how to apply them in real-world applications. The course will give you a lot of hands-on experience in mining data, and after the course you'll be able to mine your own. Weka was created at the University of Waikato, NZ. Ian Witten is the author of a book on data mining.

Course Overview

Alumni Network

International Faculty

Post Course Interactions

Instructor-Moderated Discussions

Skills You Will Gain

Prerequisites/Requirements

High school maths should be more than enough and you’ll need an understanding of some elementary statistics concepts (means and variances)

It involves no computer programming, although you need some experience with using computers for everyday tasks

What You Will Learn

Apply many different learning methods to a dataset of your choice

Compare the decision boundaries produced by different classification algorithms

Debate ethical issues raised by mining personal data

Demonstrate use of Weka for key data mining tasks

Describe the principles behind many modern machine learning methods

Evaluate the performance of a classifier on new, unseen, instances

Explain how data miners can unwittingly overestimate the performance of their system

Identify learning methods that are based on different flavors of simplicity

Interpret the output produced by classification methods

Target Students

This course is aimed at anyone who deals in data

Course Content

Expand all sections

Module 1: What is data mining?

Module 2: Where can it be applied?

Module 3: How do simple classification algorithms work?

Module 4: What are their strengths and weaknesses?

Course Instructors

Ian Witten

Instructor

I grew up in Ireland, studied at Cambridge, and taught computer science at the Universities of Essex in England and Calgary in Canada before moving to paradise (aka New Zealand) 25 years ago.

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