Welcome to "More Data Mining with Weka"

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

   

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

 

We will release classes 2, 3, 4, and 5 at approximately the same time (Monday noon NZ time) in the upcoming weeks, and send reminder announcements.

  

The course includes the following resources:

• the Weka software
• videos, one per lesson, on YouTube
•  the videos include captions (English and Chinese), 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
•  access to selected excerpts from Data Mining (3rd Edition) - plus you can buy a discounted copy from the publisher
• mid-course assessment (opens 9 May, at the end of Week 2) 
•  final assessment (opens 28 May, during Week 5)
•  announcement forum, blog, twitter feed (available from the course website)
•  discussion forum.

  

 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
• 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 (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 ("click along with Ian")
• the course should take 3–5 hours/week (4–6 hours if you do the optional reading)
• a detailed syllabus is available:

     https://weka.waikato.ac.nz/moredataminingwithweka/assets/pdf/syllabus.pdf

 

A reminder that you can review material from the Data Mining with Weka course at:

 

http://www.cs.waikato.ac.nz/ml/weka/mooc/dataminingwithweka/

 

You will be using Weka 3.6.11 throughout this course, so please download it and install it on your computer. This is a new version that has just been released: note that it is *not* the same as the version used for the previous course. It’s available at both:

 

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

and 

http://sourceforge.net/projects/weka/files/weka-3-6/

 

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 expert user of Weka and very knowledgeable about data mining generally. But it will take some effort, and motivation.

 

cheers, and good luck

Ian

 

 

http://weka.waikato.ac.nz/

https://twitter.com/WekaMOOC

http://wekamooc.blogspot.co.nz/

Enrolments open for "More Data Mining with Weka"

More Data Mining with Weka is finally open for enrolment, and will begin as scheduled on Mon 28 April. I apologise for the delay, and for missing the opening date on our website; life is more complicated than you can possibly imagine. (For example, our unseasonably long, lovely, warm, extended summer here in New Zealand meant that in the initial takes of the "trailer" video my voice was drowned out by crickets chirping.)

You do not have to have actually obtained a Statement of Completion for the introductory Data Mining with Weka MOOC to embark on More Data Mining with Weka, but you will certainly need equivalent knowledge.

In this second MOOC — even more than the first — you will do most of your learning in the Activities, and you should allow extra time for them because they’re a bit more challenging than before. Otherwise the format, and time commitment, is the same as the earlier course. Again, you do not have to complete the Activities to get a Statement of Completion: that’s based solely on your performance 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 3 minutes long.

 

 

 

 

 

 A detailed syllabus is available.

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

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

 

cheers

Ian

 

 

 

All good things come to an end

The MOOC ended last week with Class 5. It will remain open until the end of Monday, 13 April (all time zones). Statements of Completion will be emailed a few days after the course closes. The course material will remain available up indefinitely at:

 

http://www.cs.waikato.ac.nz/ml/weka/mooc/dataminingwithweka/

under a Creative Commons Attribution 3.0 Unported (CC-BY 3.0) license. Use it however you like! We've also added the music, as MP3 files, to the course material.

We are planning to re-run Data Mining with Weka later this year (possibly September). And your enthusiastic feedback has encouraged us to prepare a more advanced version, More Data Mining with Weka, which will commence on 28 April. 
 

A survey about the course is available at:

 

https://weka.waikato.ac.nz/dataminingwithweka/assessment?name=Pos

 

Please fill it in! The response rate, and your feedback, as well as the course completion rate, will no doubt influence our ability to mount future courses.

 

We have very much enjoyed giving this MOOC. And we have learned a lot in the process! We are preparing a report on the experience of running these MOOCs and we will post a draft to WekaMOOC-announce.

 

You can read more about Waikato's machine learning research group at:
 

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

 

Our publications are listed under the Publications tab. 

 

In the good old days, Weka was an externally funded research project. But that ended long ago. Both Weka and this MOOC are supported entirely by our Department and University. If you think these efforts are worthwhile and would like to support them financially, that would be lovely! Please do so here:

 

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

 

All donations are directed to research: no administrative charges are incurred.

 

Finally, how about coming to Waikato to study? Our Department's web site at
 

http://www.cs.waikato.ac.nz/

 

has links to our research groups, and to graduate student information (MSc and PhD).

 

Excuse the advertising :-). Hope you had fun with the MOOC. Don't forget the survey. See you again! — perhaps in More Data Mining with Weka.

 

cheers
Ian