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:

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

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 sure when. As for a possible third course, “Advanced Data Mining with Weka”, that’s still under consideration: there’s no schedule yet.

Please keep up the help on the course forum -- we greatly value your assistance.

cheers, and enjoy the remainder of the course!

Ian

Class 4 is now available

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

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

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

Class 3 is now available

The six lessons for Class 3 are now available on the course website:

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

After this week there are 2 weeks to go (classes 4 and 5).

The mid-course assessment is also now available. Do it when you have finished Class 2 (although it will remain open for the rest of the course). The final assessment will appear during week 5.

 

Check your Profile to ensure that your assessment marks have been recorded correctly. Also, check that the name in your Profile is the one you want on your Statement of Completion: as we will use that exact text for the Statements.

My goal is to enable you to learn as much as possible from this course, and I recognize that doing the assessments may not be a priority for you. However, our ability to mount follow-up MOOCs will depend on the success of this one as perceived by my University -- and the number of people who complete it successfully will be a key metric. Thus I urge you to do the assessments for my sake, if not your own :-)

cheers, and keep going! Weeks 3 and 4 are the central part of this course.

 

Ian

Class 2 is now available

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

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

The mid-course assessment, following Class 2, is also available. Following that, there are 3 weeks to go (classes 3, 4 and 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.

"More 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. You don't have to do the reading. All you must do to succeed are the mid-course and final assessments -- which you can try as often as you like. 
The mid-course assessment will remain open for the rest of the course; the final assessment will appear during week 5.

The videos and other course components for Classes 1 and 2 can be downloaded from the "Materials" site, in case you find that more convenient than viewing them online:

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

  
cheers, and keep going!

 

Ian

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 27 Oct, after the Week 2 content) 
•  final assessment (opens 17 Nov, after Week 5 content)
•  announcement forum, blog, twitter feed (available from the course website)
•  discussion forum.

  

 for Chinese participants:

•  videos on our Youku channel
•  one version with captions in Chinese and another with English captions
• http://i.youku.com/u/UMTI4NTE5OTA0NA==

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 and 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"

A new session of More Data Mining with Weka is open for enrolment and will start on 20 October 2014.

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

Final thoughts

The MOOC ends this week. It will remain open until the end of Monday, 11 August (all time zones). Statements of Completion will be emailed once 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 the follow-on course (More Data Mining with Weka): probably in September/October.

 

A survey about the course will be available for a few more days 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 run future courses.

 

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 next time!

 

cheers

 

Ian

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/dataminingwithweka/course

Class 5 broadens out to consider some more general issues. It's a short week, with just four topics: 

• 5.1: The data mining process
• 5.2: Pitfalls and pratfalls
• 5.3: Data mining and ethics
• 5.4: Summary

 

The post-course assessment is also now open. Everything will remain open until 11th August, when the course will be closed.

 

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

 

We will probably run the follow-up MOOC ("More Data Mining with Weka") in September/October. That course covers topics we couldn't fit into this course. Follow the announcements group, blog or Twitter for updates on that course.

cheers, and enjoy the remainder of the course!

Ian

Class 4 is now available

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

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

This class introduces some more advanced methods and techniques. The topics are:

• 4.1: Classification boundaries
• 4.2: Linear regression
• 4.3: Classification by regression
• 4.4: Logistic regression
• 4.5: Support vector machines
• 4.6: Ensemble learning

The last three are high-performance contemporary algorithms. I aim to give you a conceptual understanding of what they do and how they work, but not the gory details. You have to learn to live and work in a world where you don't understand everything. You will see some mathematics in Lessons 4.2, 4.3 and 4.5. But don't worry: I'll explain it, and anyway you don't have to fully understand the math. 

Next week is the last. And it's short: Class 5 has only 4 lessons, not the usual 6. And it's more relaxed: no math at all.

 

cheers, and keep going!

 

Ian

Class 3 is now available

The six lessons for Class 3 are now available on the course website:

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

After this week there are 2 weeks to go (classes 4 and 5).

The mid-course assessment is also now available. Do it when you have finished Class 2 (although it will remain open for the rest of the course). The final assessment will appear during week 5.
My goal is to enable you to learn as much as possible from this course, and I recognize that doing the assessments may not be a priority for you. However, our ability to mount follow-up MOOCs will depend on the success of this one as perceived by my University -- and the number of people who complete it successfully will be a key metric. Thus I urge you to do the assessments for my sake, if not your own :-)

cheers, and keep going! Weeks 3 and 4 are the central part of this course.
Ian

Class 2 is now available

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

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

Following that, there are 3 weeks to go (classes 3, 4 and 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.

"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. You don't have to do the reading. All you must do to succeed

are the mid-course and final assessments -- which you can try as often as you like. The mid-course assessment will become available this week (9 July) and remain open for the rest of the course. The final assessment will appear during week 5.


cheers, and keep going!

Ian

Welcome to "Data Mining with Weka"

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

  

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

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; 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
•  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 July, in Week 2) 
•  final assessment (opens  28 July, in Week 5)
•  announcement forum, blog, twitter feed (available from the course website)
•  discussion forum: Teaching Assistants will be available to help you. Primarily this will be in English but some of the Assistants have said they can also help in other languages.

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
•  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).

 

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

cheers, and good luck

 

Ian

Volunteer Community Teaching Assistants

We would like to invite volunteers to be Community Teaching Assistants for the next session of Data Mining with Weka. Two types of people are likely to be effective in this role:

• learners who completed the first session of Data Mining with Weka
• existing Weka users

For those who did take the first MOOC then the Community Teaching Assistant role is some of the work performed by Peter. It is not so much answering questions as providing responses that encourage the learners to solve their own problems.

This is a call for volunteers, we don't have the resources to pay you anything - but we will produce a special version of the Statement of Completion for the Community Teaching Assistants.

To volunteer you should email wekamooc[at]waikato.ac.nz with a summary of your experience (which can simply be that you completed the first run of the MOOC). The session starts on 30th June 2014.

Enrolment opens for "Data Mining with Weka"

Enrolments have opened for a new session of Data Mining with Weka:

http://weka.waikato.ac.nz

The course will start on 30 June 2014 and extends over 5 weeks. It features:

• Video lectures
• Practical activities and online assessment
• Extracts from Data Mining (3rd Edition): Witten, Frank & Hall (2011)

You can also follow the course via Twitter or the blog:

 

https://twitter.com/WekaMOOC

 

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

Closing thoughts

The MOOC ended last week with Class 5. It will remain open until the end of Wednesday, 11 June (all time zones). Statements of Completion will be emailed a few days after the course closes. Please check your name (and marks) in the My Profile section of the course website: we will use that name on the Statement of Completion. 


The course material will remain available up indefinitely at:

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

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 an MP3 file, to the course material.

We are planning to re-run Data Mining with Weka beginning on 30 June. If you would like to be a volunteer Community Teaching Assistant for that course then watch out for an announcement about how to participate.

We will also re-run More Data Mining with Weka sometime, not sure when.

A survey about the course is available at:

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

Those who have completed this course are now experts on Weka and data mining. One person said "I felt slightly surprised taking this course at how basic my understanding actually was from the first class. Hopefully, there wouldn't be quite as much of this feeling in the next course.” You’re right, the introductory course was rather simplistic, but this one has been thorough. You have learned a lot, and you really are an expert now.

Nevertheless, there is more to be learned! Quite a lot of interest has been expressed in a further course, Advanced Data Mining with Weka. This may happen, but it will not happen soon: I am taking an extended 3-month holiday from the University (and from MOOCs); after that it will take many months to prepare a new MOOC. In the meantime, if you are interested in scripting, there is a new Weka wrapper for Python.

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/moredataminingwithweka/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 Advanced Data Mining with Weka.

cheers

Ian

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 opens on 28th May. Everything will remain open until 11th June, when the course will be closed. The videos, slides and transcripts will remain available at YouTube, Youku and the "Materials" site:

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

We will also ask you to complete a survey for your opinions of the MOOC.

We are planning to run the introductory course “Data Mining with Weka” again in July. We will run “More Data Mining with Weka” again, but are not sure when: it depends on when we have sufficient new graduates from the introductory course to make it worthwhile. As for a possible third course, “Advanced Data Mining with Weka”, that’s still under consideration: there’s no schedule yet.

Please keep up the help on the course forum -- we greatly value your assistance.

cheers, and enjoy the remainder of the course!

Ian

Class 4 is now available

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

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

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!

It's great to see so many people helping each other on the course forum. Please keep it up -- we greatly value your assistance.

cheers 

 

Ian

Class 3 is now available

The six lessons for Class 3 are now available on the course website:

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

After this week there are 2 weeks to go (classes 4 and 5).

It's good to see so many people having fun with the course!

The mid-course assessment is also now available. Do it when you have finished Class 2 (although it will remain open for the rest of the course). The final assessment will appear during week 5.

 

Occasionally a problem occurs when submitting the assessments, where you click “Submit Answers” and get a blank page. This is a glitch in the Google infrastructure that runs the MOOC, and it is out of our control. Please make a note of your answers before submitting, so that if this happens you can re-submit them without too much pain. Check your Profile for your mark to ensure that it has been recorded.

My goal is to enable you to learn as much as possible from this course, and I recognize that doing the assessments may not be a priority for you. However, our ability to mount follow-up MOOCs will depend on the success of this one as perceived by my University -- and the number of people who complete it successfully will be a key metric. Thus I urge you to do the assessments for my sake, if not your own :-)

cheers, and keep going! Weeks 3 and 4 are the central part of this course.

 

Ian

Class 2 is now available

The six lessons for Class 2 are now available on the course website:
https://weka.waikato.ac.nz/moredataminingwithweka

Following that, there are 3 weeks to go (classes 3, 4 and 5).

It's good to see so many people having fun with the course!

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.

"More 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. You don't have to do the reading. All you must do to succeed are the mid-course and final assessments -- which you can try as often as you like. The mid-course assessment will become available this Friday (May 9) and remain open for the rest of the course. The final assessment will appear during week 5.

The videos and other course components for Classes 1 and 2 can be downloaded from the "Materials" site, in case you find that more convenient than viewing them online:

http://www.cs.waikato.ac.nz/ml/weka/mooc/moredataminingwithweka/
  
We plan to put out a short (optional) update video soon.

cheers, and keep going!

 

Ian

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

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/dataminingwithweka/course

Class 5 broadens out to consider some more general issues. It's a short week, with just four topics: 

• 5.1: The data mining process
• 5.2: Pitfalls and pratfalls
• 5.3: Data mining and ethics
• 5.4: Summary

 

The post-course assessment opens on 2nd April. Everything will remain open until 13th April, when the course will be closed.

 

We will also ask you to complete a survey for your opinions of the MOOC. 

 

We will probably run the course again, perhaps in late winter-- I mean NZ winter! -- maybe in September 2014. And don't forget the follow-up MOOC  ("More Data Mining with Weka") that covers topics we couldn't fit into this course. More news on that very soon.

Please keep up the help on the course forum -- we greatly value your assistance.

cheers, and enjoy the remainder of the course!

Ian

Class 4 is now available

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

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

 

This class introduces some more advanced methods and techniques. The topics are:

• 4.1: Classification boundaries
• 4.2: Linear regression
• 4.3: Classification by regression
• 4.4: Logistic regression
• 4.5: Support vector machines
• 4.6: Ensemble learning

The last three are high-performance contemporary algorithms. I aim to give you a conceptual understanding of what they do and how they work, but not the gory details. You have to learn to live and work in a world where you don't understand everything. You will see some mathematics in Lessons 4.2, 4.3 and 4.5. But don't worry: I'll explain it, and anyway you don't have to fully understand the math. 

Next week is the last. And it's short: Class 5 has only 4 lessons, not the usual 6. And it's more relaxed: no math at all.

 

It's great to see so many people helping each other on the course forum. Please keep it up -- we greatly value your assistance.

 

Ian

Class 3 is now available

The six lessons for Class 3 are now available on the course website:

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

After this week there are 2 weeks to go (classes 4 and 5).

It's good to see so many people having fun with the course!

The mid-course assessment is also now available. Do it when you have finished Class 2 (although it will remain open for the rest of the course). The final assessment will appear during week 5.

My goal is to enable you to learn as much as possible from this course, and I recognize that doing the assessments may not be a priority for you. However, our ability to mount follow-up MOOCs will depend on the success of this one as perceived by my University -- and the number of people who complete it successfully will be a key metric. Thus I urge you to do the assessments for my sake, if not your own :-)

cheers, and keep going! Weeks 3 and 4 are the central part of this course.
Ian

Class 2 is now available

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

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

Following that, there are 3 weeks to go (classes 3, 4 and 5).

It's good to see so many people having fun with the course! 

 

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.

"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. You don't have to do the reading. All you must do to succeed

are the mid-course and final assessments -- which you can try as often as you like. The mid-course assessment will become available this Friday (March 14) and remain open for the rest of the course. The final assessment will appear during week 5.

We plan to put out a short (optional) update video soon.

cheers, and keep going!
Ian

Welcome to Data Mining with Weka

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

  

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

 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; Lesson 1.2 gives downloading instructions
•  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 14 March, at the end of Week 2) 
•  final assessment (opens 2 April, during Week 5)
•  announcement forum, blog, twitter feed (available from the course website)
•  discussion forum: Teaching Assistants will be available to help you. Primarily this will be in English but some of the Assistants have said they can also help in Spanish, Portuguese and Thai.

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
•  feel free to install Weka in advance, but please ensure that you have version 3.6.10
•  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).

 

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

cheers, and good luck

 

Ian

Volunteer Community Teaching Assistants

We would like to invite volunteers to be Community Teaching Assistants for the next session of Data Mining with Weka. Two types of people are likely to be effective in this role:

• learners who completed the first session of Data Mining with Weka
• existing Weka users

For those who did take the first MOOC then the Community Teaching Assistant role is some of the work performed by Peter. It is not so much answering questions as providing responses that encourage the learners to solve their own problems.

This is a call for volunteers, we don't have the resources to pay you anything - but we will produce a special version of the Statement of Completion for the Community Teaching Assistants.

To volunteer you should email wekamooc[at]waikato.ac.nz with a summary of your experience (which can simply be that you completed the first run of the MOOC). The session starts on 3rd March 2014.

Enrolments open for a new session of Data Mining with Weka

Enrolments have opened for a new session of Data Mining with Weka:

 

http://weka.waikato.ac.nz

 

The course will start on 3rd March 2014 and extends over 5 weeks. It features:

• Video lectures
• Practical activities and online assessment
• Extracts from Data Mining (3rd Edition): Witten, Frank & Hall (2011)

You can also follow the course via Twitter or the blog:

 

https://twitter.com/WekaMOOC

 

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