A new session of Advanced Data Mining with Weka starts on 13 November 2017 on the FutureLearn platform:
https://www.futurelearn.com/courses/advanced-data-mining-with-weka/
Tuesday, 7 November 2017
Friday, 6 October 2017
Data Mining with Weka on FutureLearn
A new session of Data Mining with Weka starts on 9 October 2017 on the FutureLearn platform:
https://www.futurelearn.com/
https://www.futurelearn.com/
Friday, 28 April 2017
More Data Mining with Weka on FutureLearn
A new session of More Data Mining with Weka starts on 8 May 2017 on the FutureLearn platform:
https://www.futurelearn.com/courses/more-data-mining-with-weka
Trailer:
https://www.futurelearn.com/courses/more-data-mining-with-weka
Trailer:
Thursday, 16 February 2017
Data Mining with Weka on FutureLearn
A new session of Data Mining with Weka starts on 6 March 2017 on the FutureLearn platform :
https://www.futurelearn.com/
Trailer:
Monday, 4 July 2016
All three Weka MOOCs available as self-paced courses
All three MOOCs ("Data Mining with Weka", "More Data Mining with Weka" and "Advanced Data Mining with Weka") are now available on a self-paced basis. All the material, activities and assessments are available from now until 24th September 2016 at:
Ian & the WekaMOOC team
We are not
providing any tutorial, help or assistance during this session.
Also, we
will not produce any Statements of Completion until after 24th September.Tuesday, 24 May 2016
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/advanceddataminingwithweka
Class 5 is about scripting. People who use Weka a lot always want to be able to write scripts to do the work, instead of all this clicking. Well, you can! You can
The post-course assessment is also now open. The videos, slides and transcripts will remain available at YouTube, and the "Materials" site:
Class 5 is about scripting. People who use Weka a lot always want to be able to write scripts to do the work, instead of all this clicking. Well, you can! You can
- write Weka scripts in Python from within the Explorer interface
- write Weka scripts in Groovy, a Java-based scripting language, in the same way
- set up the Python Weka wrapper so that you can access the Weka code from within your own Python installation.
The post-course assessment is also now open. The videos, slides and transcripts will remain available at YouTube, and the "Materials" site:
There is also a post-course survey for your opinions of the MOOC.
We will run all three of these courses, “Data Mining with Weka,” “More Data Mining with Weka,” and “Advanced Data Mining with Weka,” again, but are not yet sure when
cheers, and enjoy the remainder of the course!
Ian
http://weka.waikato.ac.nz/
https://twitter.com/WekaMOOC
http://wekamooc.blogspot.co.nz/
Monday, 16 May 2016
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 distributed processing with Apache Spark (and also with Hadoop). We're assuming that you don't necessarily have access to a cluster computer, but you can still use the framework on a single machine, and the Activities will show you how to get started with this.
The Application lesson 4.6 shows you how to use Weka for image processing, by creating all sorts of different feature sets for your images using the imageFilter package.
The Application lesson 4.6 shows you how to use Weka for image processing, by creating all sorts of different feature sets for your images using the imageFilter package.
Next week is the last. Pretty soon you will be a certified advanced expert in data mining and the use of Weka! Keep at it!
cheers
Monday, 9 May 2016
Class 3 is now available
The six lessons for Class 3 are now available on the course website:
https://weka.waikato.ac.nz/advanceddataminingwithweka
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.
https://weka.waikato.ac.nz/advanceddataminingwithweka
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.
Our goal is to enable you to learn as much as possible from this course, and we 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 :-)
In this class we'll learn about interfacing to other data mining packages. The first lesson shows you how to access LibSVM and LibLINEAR, and the remaining ones show you how to access some of the many facilities in the popular R statistical computing package. These increase the scope of Weka enormously!
The Application lesson 3.6 shows you how to use Weka to analyze functional MRI Neuroimaging data, and in the Activity you will actually do some of this analysis!
cheers, and keep going!
Our goal is to enable you to learn as much as possible from this course, and we 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 :-)
In this class we'll learn about interfacing to other data mining packages. The first lesson shows you how to access LibSVM and LibLINEAR, and the remaining ones show you how to access some of the many facilities in the popular R statistical computing package. These increase the scope of Weka enormously!
The Application lesson 3.6 shows you how to use Weka to analyze functional MRI Neuroimaging data, and in the Activity you will actually do some of this analysis!
cheers, and keep going!
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.
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.
http://www.cs.waikato.ac.
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:
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
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
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:
Some notes for participants:
PS
any previous students who wish to volunteer as Community Teaching Assistants for this session are also welcome:
http://wekamooc.blogspot.co.
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 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/
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.
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/
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:
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
Monday, 15 June 2015
Class 3 is now available
The six lessons for Class 3 are now available on the course website:
https://weka.waikato.ac.nz/
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.
https://weka.waikato.ac.nz/
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.
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
Monday, 8 June 2015
Class 2 is now available
The six lessons for Class 2 are now available on the course website:
https://weka.waikato.ac.nz/
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.
https://weka.waikato.ac.nz/
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
Tuesday, 2 June 2015
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:
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:
A reminder that you can review material from the Data Mining with Weka course at:
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:
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
Thursday, 21 May 2015
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.
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.
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
https://weka.waikato.ac.nz/moredataminingwithweka
cheers
Ian
Monday, 11 May 2015
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:
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.
cheers, and enjoy the remainder of the course!
Ian
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