Hello! my name is Ian Witten, and I'm from the University of Waikato here in New
Zealand, and I want to tell you about our new
free, online course—Data Mining with Weka.
We're overwhelmed by data in the world today.
Every time we check out an item at the supermarket,
every time we swipe our credit card, every time we send an email,
every time we type a keystroke on our keyboard. Every time we make a phone call, send a text, walk past
a security camera.
We all generate a little bit of data. Data mining is about taking this raw data,
and transforming it into something more useful,
information, perhaps, or predictions, predictions about what might happen next,
predictions that can be used in the real world.
Let me give you an example. You're standing at the supermarket checkout.
Every item is recorded by the till and
at the end, you give them your loyalty card, and
they'll give you 2% off,
and you'll give them your name and address and access to all sorts of other data,
demographic data, about people like you, and so on. You've got lots of bargains today; it's
been pretty good.
Thanks to those coupons they sent you in the mail
last week, you've been able to stock up on some items that you wouldn't normally
buy, but you've bought today, because
you got some money off. And next week, they'll send you some more coupons.
They'll take this data,
they'll analyze it, they'll include data from thousands or
millions of people like you. They'll do little experiments,
to find out if they reduce the price of an item just a little bit
are you going to buy more of that? These coupons are a mechanism for
individual prices—prices set just for you.
Everyone benefits, you get a bargain, everyone loves a bargain, the supermarket
sells more stuff. And it's all thanks to
data mining. This MOOC is called Data Mining with Weka.
Let me tell you what a weka is. A weka, actually, is a little bird,
like it's better known relative, the kiwi,
found only in the islands of New Zealand. Flighless. About the size of a duck, actually.
I don't know if you can see any ducks in the picture, but it's about just the size of those
ducks out there on the lake.
In our case, Weka is
a toolkit, a data mining toolkit, a work bench.
It's an acronym for Waikato Environment for Knowledge
Analysis. it was produced here at the University of Waikato. We've had a machine-
learning project going on here for
over 20 years now. We do research on machine-learning, and one of the
outcomes of that research
is this Weka workbench. A lot of people are starting to take data mining very
seriously. You've heard about big data;
you might have heard a lot about metadata recently, and what you might learn
from metadata.
A lot of people find data mining mysterious. The real
aim of this course is to take the mystery out of data mining,
to get you some practical experience actually using the Weka toolkit
to do some mining on the data sets that we provide,
to set you up so that later on, you can use Weka to
work on your own data sets and do your own data mining.
It doesn't involve any programming or anything like that. You're going to be using the
tools that we provide,
the Weka tools. It might help to know a little bit of
elementary statistics, like means, variants, standard deviations, and so on.
You might see a couple of mathematical formulas, but I'll explain those, so
don't worry about that. You don't really need any specific mathematical background.
The course is going to involve a number of short 5-10 minute videos, like this.
Each one will be followed by a practical activity. You're going to be doing something
on your computer using the Weka workbench.
Weka is free, open source software.
It runs on anything-Windows, Mac, Linux.
There will be some short videos followed by an activity
that might take another 5-10 minutes. We call that a lesson, about
15-20 minutes worth of work.
There are six lessons in each class; there are five classes altogether.
About one class a week is the kind of rate that we would expect you to take this.
You're going to be doing about three hours of work a week
for about five weeks. To take part in this course,
you need a computer, of course, with an internet connection; all of the videos are on
Youtube. You need a little bit of time.
You need a Google account to access these things,
and you need some motivation and interest in the subject. Associated with
the course is a text book,
called Data Mining.
It's a really good book on data mining. I know that, because I
wrote it myself with a couple of friends.
The publisher, Morgan Kaufmann, has kindly agreed to
give people on the course free access to large chunks of this textbook online.
In order to get your certificate of completion,
there's a couple of assessments, one in the middle of the course and one at the end.
If you do sufficiently well on those, you'll be
getting an official
certificate of completion from the University of Waikato.
That's it—Data Mining with Weka, coming soon to a computer
near you. I'm looking forward to it, and I hope to see you there.
Bye for now!