'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:

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

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 forum, blog, twitter 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

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 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

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 8 June, with the Week 2 content) 
•  final assessment (opens 29 June, with the 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 3.6.12 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 

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 new session of More Data with Weka

We will be closing the current session of Data Mining with Weka on the 25th May.
A new session of More Data Mining with Weka is now open for enrolment and will start on 1 June 2015.

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

Class 5 and final assessment 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 25th May, when the course will be closed.

 

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

 

We are also running a session of the follow-on MOOC "More Data Mining with Weka" starting 6th June. 

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 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 see that your marks have been recorded correctly.
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 (24 April) 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  24 April, in Week 2) 
•  final assessment (opens  15 May, 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)
• 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.

cheers, and good luck

 Ian


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

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 13 April 2015 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/


Ian