Monday, 2 May 2016

Class 2 is now available


The six lessons for Class 2 are now available on the course website:

https://weka.waikato.ac.nz/advanceddataminingwithweka

The mid-course assessment, which covers the material up to and including Class 2, is also available. Following that, there are 3 weeks to go (classes 3, 4 and 5).
The mid-course assessment will remain open for the rest of the course; the final assessment will appear during week 5.
 
The activities are a crucial part of the course: they're where most people will do their actual learning! However, they do not form part of the assessment, so don't be scared to get wrong answers. Also, some of the activities are pretty difficult and time-consuming. You don't necessarily need to actually complete them if you find that difficult on your computer, but you do need to understand what it is that you are supposed to do -- and why.

"Advanced Data Mining with Weka" has been designed so that participants at many different levels can learn as much as possible – and complete the course successfully. All you must do to get the Statement of Completion are the mid-course and final assessments -- which you can try as often as you like. 


This class is about data stream mining, and MOA, Weka's big sister. MOA's algorithms are stream-oriented: they don't keep the dataset in main memory. You can access the algorithms from the Weka interface. But an important aspect of stream-oriented data mining is evaluation: how do you evaluate a learning algorithm that runs continuously on a data stream (which may, in addition, be evolving)? That is what the MOA interface is for, and you will learn about that too.

The Application in Lesson 2.6 is about applying Weka to a problem in bioinformatics, which is a very popular -- and important! -- area for data mining.
  
cheers, and keep going!


Monday, 25 April 2016

Welcome to "Advanced Data Mining with Weka"


Welcome to the course "Advanced Data Mining with Weka". The six lessons for Class 1 are now available on the course website:
   

We will release classes 2, 3, 4, and 5 on Mondays (NZ time) in the upcoming weeks, and send reminder announcements.
  
Weka 3.8 has just been released and you will be using it throughout this course, so please download it and install it on your computer. It’s available at both:

http://www.cs.waikato.ac.nz/ml/weka/downloading.html 


and 



 
This course includes the following resources:
  • videos, one per lesson, on YouTube
  •  the videos include captions, which can be turned on in YouTube
  •  we recommend viewing in HD format, again a YouTube control
  •  slides used in the videos (PDF format)
  •  text files containing transcripts of the videos
  •  activities that follow each lesson
  • mid-course assessment (opens 2 May, with the Week 2 content) 
  •  final assessment (opens 23 May, with the Week 5 content)
  •  announcement forum, blog, twitter feed (available from the course website)
  •  discussion forum.

Some notes:
  • work through the videos and activities at your own pace, in your own time
  • a new class appears every week; old classes will remain available until the course closes
  • in theory, you could leave all your learning to the last week (but we don't recommend this!)
  • please subscribe to the announcement forum if you haven't already done so: this is the best way to stay up-to-date with the course (click on Membership and email settings to subscribe)
  • only the mid-course and final assessments count towards the Statement of Completion
  • please check your name and marks in the My Profile section of the website (this is the data we will use to produce your Statement of Completion)
  • during the videos, it may help to follow with Weka on your own computer
  • the course should take 3–6 hours/week
  • a detailed syllabus is available:
     https://weka.waikato.ac.nz/advanceddataminingwithweka/assets/pdf/syllabus.pdf

Please help us by filling out the pre-course survey if you have not already done so.

By the time you have finished this course you will be an advanced expert user of Weka and very knowledgeable about data mining generally. But it will take some effort, and motivation.

cheers, and good luck
Ian

Wednesday, 6 April 2016

"Advanced Data Mining with Weka" open for enrolment


Advanced Data Mining with Weka is now open for enrolment, and is scheduled to start on 25 April.

Like the other two Weka MOOCs, this draws on the resources of the Machine Learning Group in the Department of Computer Science at the University of Waikato. It covers:

  • time series forecasting; data stream mining
  • inter-operability with R; scripting Weka in Python and Groovy
  • distributed processing with Apache SPARK and Hadoop
  • application case studies
A detailed syllabus is available.

This is advanced stuff, and you need to be an experienced Weka user before starting. The format is the same as for the earlier courses, and again you will do most of your learning in the Activities, although whether you get a Statement of Completion depends solely on your how well you do in the mid-class and end-of-class assessments.

There’s more information about the course in the trailer video: it’s informative, entertaining, and only about 4 minutes long.





By the time you have finished this course you will be an advanced expert on the use of Weka. Enrol at:

https://weka.waikato.ac.nz/

cheers
Ian & the Weka Team








Thursday, 3 March 2016

Two Self-paced Courses

Both "Data Mining with Weka" and "More Data Mining with Weka" are now available on a self-paced basis. All the material, activities and assessments are available now until 15th April 2016 at:




We are not providing any tutorial, help or assistance during this session. Also, we will not generate any Statements of Completion until after 15th April.


Ian & the WekaMOOC team

Monday, 13 July 2015

'Data Mining with Weka' available as self-paced course

Welcome to "Data Mining with Weka".


Unlike previous sessions the course is now being offered on a self-paced basis. All the material, activities and assessments are available now until 23rd October 2015 at:




We are not providing any tutorial, help or assistance during this session. Also, we will not generate any Statements of Completion until after 23rd October.


The course includes the following resources:

  •  the Weka software; Lesson 1.2 gives downloading instructions (we are using version 3.6.11)
  •  videos, one per lesson, on YouTube
  •  the videos include captions (English and Chinese), which can be turned on in YouTube
  •  slides used in the videos (PDF format)
  •  text files containing transcripts of the videos
  •  activities that follow each lesson
  •  access to selected excerpts from Data Mining (3rd Edition) - plus you can buy a discounted copy from the publisher
  •  announcement forumblogtwitter feed (available from the course website)


for Chinese participants:

  •  videos on Youku
    • one version with captions in Chinese (another with English captions is available on our Youku channel)

Some notes for participants:

  • work through the videos and activities at your own pace, in your own time
  • please subscribe to the announcement forum if you haven't already done so: this is the best way to stay up-to-date with the course (click on Membership and email settings to subscribe)
  • only the mid-course and final assessments count towards the Statement of Completion
  •  feel free to install Weka in advance, but please ensure that you have version 3.6.11
  •  if you already know something about Weka, feel free to skip the first class (or two)
  •  during the videos, it may help to follow with Weka on your own computer ("click along with Ian")
  •  the course should take 2–3 hours/week (3–4 hours if you do the optional reading)
  • you can download the materials from http://www.cs.waikato.ac.nz/ml/weka/mooc/dataminingwithweka/

 Please help us by filling out the pre-course survey if you have not already done so.


Ian & the WekaMOOC team






PS
any previous students who wish to volunteer as Community Teaching Assistants for this session are also welcome:
http://wekamooc.blogspot.co.nz/2014/06/volunteer-community-teaching-assistants.html

Monday, 29 June 2015

Class 5 is now available


The lessons for Class 5, the last in our course, are now available on the course website:
https://weka.waikato.ac.nz/moredataminingwithweka

The 6 lessons in Class 5 addresses some important miscellaneous issues. Two are devoted to neural networks, both the simple Perceptron and multilayer Perceptrons — sometimes called “connectionist” models. Then we consider that perennial question, “how much data is enough?”, and show how to answer it using learning curves. Next we look at how to optimise the parameters of learning algorithms, and finally we return to the very beginning and re-visit the ARFF format, including some useful features that haven’t yet been encountered.

The post-course assessment is also now open. The videos, slides and transcripts will remain available at YouTube, Youku and the "Materials" site:

There is also a post-course survey for your opinions of the MOOC.

We aim to run both the introductory course “Data Mining with Weka” and “More Data Mining with Weka” again, but are not yet sure when. As for a possible third course, “Advanced Data Mining with Weka”, that’s still under consideration: there’s no schedule yet.



cheers, and enjoy the remainder of the course!


Ian

Monday, 22 June 2015

Class 4 is now available

The six lessons for Class 4 are now available on the course website:



In this class we'll learn about two topics: attribute selection and cost-sensitive classification. Automatic selection of an attribute subset is a powerful way of getting both good results and simpler, easily explainable, models from machine learning; indeed you will end up achieving stunning results with a tiny subset of attributes on a document classification task. And taking the costs of different kinds of error into account is essential in many practical applications.
Next week is the last. Pretty soon you will be an expert in data mining and the use of Weka!

cheers

Ian