0:00:00.099,0:00:05.959
Hi! I'm Ian Witten from the beautiful University
of Waikato here in New Zealand, and I want

0:00:05.959,0:00:10.560
to tell you about our new online course: Advanced
Data Mining with Weka.

0:00:10.560,0:00:14.690
If you liked the other courses--Data Mining
with Weka and More Data Mining with Weka--you'll

0:00:14.690,0:00:15.680
love this new course.

0:00:15.680,0:00:21.150
It's the same format, the same software, the
same learning by doing, and the aim is the

0:00:21.150,0:00:27.150
same, too: to show you how to use powerful
techniques of data mining on your own data.

0:00:27.150,0:00:31.029
One difference is that the lessons in this course
are given by different people.

0:00:31.029,0:00:34.730
In fact, you'll get to meet pretty well the
whole Weka team in this course.

0:00:34.730,0:00:36.969
This new course is advanced.

0:00:36.969,0:00:38.760
We're going to be looking at new kinds of
data.

0:00:38.760,0:00:43.979
We're going to be looking at time series,
for example, where the data evolves over time

0:00:43.979,0:00:46.100
and your job is to predict the future.

0:00:46.100,0:00:51.909
Or situations where the characteristic of
the source changes slowly over time,

0:00:51.909,0:00:55.760
like it does in real life, and your job is
to track those changes.

0:00:55.760,0:00:59.249
We'll look at different ways of working with
big data.

0:00:59.249,0:01:04.680
We're going to introduce you to Weka's big
sister, Moa, which is a stream-oriented data

0:01:04.680,0:01:09.950
mining system that never stores the data in
main memory, so it can operate on effectively

0:01:09.950,0:01:17.000
infinite streams of data and has to use special
algorithms to deal with these streams,

0:01:17.000,0:01:19.100
which we'll explain to you.

0:01:19.100,0:01:26.659
We'll also show you how to deploy Weka on
a cluster computing environment using the Apache

0:01:26.659,0:01:30.820
Spark framework, and also the popular Hadoop
framework.

0:01:30.820,0:01:34.969
We're going to show you how you can reach
out to other data mining systems from Weka,

0:01:34.969,0:01:38.899
for example, the popular R data mining system.

0:01:38.899,0:01:44.359
You can get at all the algorithms in R,
all the mining algorithms and all the

0:01:44.359,0:01:49.630
very powerful information display capabilities
right there within your Weka interface.

0:01:49.630,0:01:55.060
We'll look at scripting Weka in Python, and
you can write little Python scripts right

0:01:55.060,0:01:57.499
there in the Weka interface.

0:01:57.499,0:02:03.409
We'll show you how to set up the Python Weka
wrapper, where you can access the Weka API

0:02:03.409,0:02:06.420
right from within your very own Python program.

0:02:06.420,0:02:09.710
By popular demand, we've included some applications.

0:02:09.710,0:02:15.350
We'll talk about the application of Weka to
soil sample analysis, where machine learning

0:02:15.350,0:02:20.390
can effectively replace time consuming wet
chemistry.

0:02:20.390,0:02:27.670
We'll look at signals from your brain, functional
MRI signals, which treats the brain as a set

0:02:27.670,0:02:31.990
of voxels that extends over time, a kind
of four-dimensional dataset of what's happening

0:02:31.990,0:02:35.530
in your brain and how to analyze this kind
of data.

0:02:35.530,0:02:39.420
We'll look at a bioinformatics application:
signal peptide prediction.

0:02:39.420,0:02:45.130
We'll look at some image processing stuff,
some filters for getting features off images;

0:02:45.130,0:02:51.860
and we'll look at a Twitter application where
you use Weka to do text mining on a Twitter

0:02:51.860,0:02:53.140
feed.

0:02:53.140,0:02:57.290
This course is aimed at teaching you the principles
and practice of data mining.

0:02:57.290,0:02:59.980
We don't look at the technical details of
particular algorithms.

0:02:59.980,0:03:04.120
In fact, you don't need any special mathematical
background to do this course.

0:03:04.120,0:03:07.310
Indeed, you don't need any programming background.

0:03:07.310,0:03:10.730
We'll see some little Python programs, but
you can pick that up along the way.

0:03:10.730,0:03:12.370
We'll show you how, don't worry.

0:03:12.370,0:03:16.320
Other things for this course ... You're going
to need a computer, of course.

0:03:16.320,0:03:20.010
You're going to need an internet connection.

0:03:20.010,0:03:23.050
You're going to need a Google account, because
again we're using the Google infrastructure

0:03:23.050,0:03:24.130
to deliver the course.

0:03:24.130,0:03:26.760
You will need a few hours a week each week.

0:03:26.760,0:03:29.490
You'll need a lot of motivation.

0:03:29.490,0:03:30.380
This is difficult stuff.

0:03:30.380,0:03:32.110
You're going to learn a lot.

0:03:32.110,0:03:33.700
The course lasts five weeks.

0:03:33.700,0:03:38.420
There are six lessons each week, and each
lesson comprises a short video like this one,

0:03:38.420,0:03:43.540
followed by an activity where you get to practice
what you've learned on a dataset that we provide.

0:03:43.540,0:03:44.790
And there are a couple of tests:

0:03:44.790,0:03:50.640
if you do well enough in those, you'll receive
a statement of completion from the University

0:03:50.640,0:03:52.770
of Waikato, signed by me.

0:03:52.770,0:03:55.820
What else? Textbook? There is no textbook.

0:03:55.820,0:03:58.100
This stuff isn't in the books.

0:03:58.100,0:04:03.460
And I've recorded a new piece of music for you,
some improvisations on a jazz theme by Dizzy Gillespie.

0:04:03.460,0:04:06.870
And the price of admission is zero.

0:04:06.870,0:04:08.830
This course is absolutely free.

0:04:08.830,0:04:10.870
So that's it.

0:04:10.870,0:04:15.370
Advanced Data Mining with Weka, coming soon
to a computer near you.

0:04:15.370,0:04:16.970
Hope to see you there.

0:04:16.970,0:04:17.660
Bye for now!