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Online course

Advanced Data Mining with Weka

Learn how to use popular packages that extend Weka's functionality and areas of application. Use them to mine your own data!

What’s the difference between a free course and an upgraded course?

Free:

  • Access to the course for its duration + 14 days, regardless of when you join (this includes access to articles, videos, peer review steps, quizzes)
  • No access to course tests
  • No certificate

Upgraded:

  • Unlimited access to the course, for as long as it exists on FutureLearn (this includes access to articles, videos, peer review steps, quizzes)
  • Access to course tests
  • A Certificate of Achievement when you complete the course

Find out more

Advanced Data Mining with Weka

Upgrade - $84
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Extend your repertoire of data mining scenarios and techniques

This course will bring you to the wizard level of skill in data mining, following on from Data Mining with Weka and More Data Mining with Weka, by showing how to use popular packages that extend Weka’s functionality. You’ll learn about forecasting time series and mining data streams. You’ll connect up the popular R statistical package and learn how to use its extensive visualisation and preprocessing functions from Weka. You’ll script Weka in Python – all from within the friendly Weka interface. And you’ll learn how to distribute data mining jobs over several computers using Apache SPARK.

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Skip to 0 minutes and 5 secondsHi!

Skip to 0 minutes and 6 secondsI'm Ian Witten from the beautiful University of Waikato here in New Zealand, and I want to tell you about our new online course: Advanced Data Mining with Weka. If you liked the other courses--Data Mining with Weka and More Data Mining with Weka--you'll love this new course.

Skip to 0 minutes and 21 secondsIt's the same format, the same software, the same learning by doing, and the aim is the same, too: to show you how to use powerful techniques of data mining on your own data. One difference is that the lessons in this course are given by different people. In fact, you'll get to meet pretty well the whole Weka team. This new course is advanced. We're going to be looking at new kinds of data. We're going to be looking at time series, for example, where the data evolves over time and your job is to predict the future. Or situations where the characteristic of the source changes slowly over time, like it does in real life, and your job is to track those changes.

Skip to 1 minute and 0 secondsWe'll look at different ways of working with big data. We're going to introduce you to Weka's big sister, Moa, which is a stream-oriented data mining system that never stores the data in main memory, so it can operate on effectively infinite streams of data. We'll also show you how to deploy Weka on a cluster computing environment using the Apache Spark framework, and also the popular Hadoop framework. We're going to show you how you can reach out to other data mining systems from Weka, for example, the popular R data mining system. You can get at all the algorithms in R. We'll look at scripting Weka in Python, and you can write little Python scripts right there in the Weka interface.

Skip to 1 minute and 48 secondsBy popular demand, we've included some applications. So that's it. Advanced Data Mining with Weka, coming soon to a computer near you. Hope to see you there. Bye for now!

When would you like to start?

  • Date to be announced

What will you achieve?

By the end of the course, you'll be able to...

  • Discuss the use of lagged variables in time series forecasting
  • Explore the use of overlay data in time series forecasting
  • Identify several different applications of data mining with Weka
  • Compare incremental and non-incremental implementations of classifiers
  • Evaluate the performance of classifiers under conditions of concept drift
  • Classify tweets using various techniques
  • Calculate optimal parameter values for non-linear support vector machines
  • Demonstrate the use of R classifiers in Weka
  • Develop R commands and R scripts from Weka
  • Explain how distributed Weka runs Weka on a cluster of machines
  • Experiment with distributed implementations of Weka classifiers and clusterers
  • Explain how “map” and “reduce” tasks are used to distribute Weka
  • Design Python and Groovy scripts for Weka operations
  • Apply Python libraries to produce sophisticated visualizations of Weka output
  • Describe how Weka can be invoked from within a Python environment

Who is the course for?

This course is aimed at anyone who deals in data. You should have completed Data Mining with Weka and More Data Mining with Weka – or be an experienced Weka user. Although the course includes some scripting with Python, you need no prior knowledge of the language. You will have to install and configure some software components; we provide full instructions.

What software or tools do you need?

Before the course starts, download the free Weka software. It runs on any computer, under Windows, Linux, or Mac. It has been downloaded millions of times and is being used all around the world.

(Note: Depending on your computer and system version, you may need admin access to install Weka.)

What do people say about this course?

Interesting and well presented course. I'm now going to spend some more time comparing weka and R output and results from linear and logistical regression. Thanks for all the work that went into developing and offering this course.

WJ Kinder

I took my time - busy schedule these days - but finally completed the course! Thank you for the excellent teaching, for the friendly tone, and for the tremendous work which I am sure went behind putting this course together. I am looking forward to starting the next one, both to learn more about the selection of attributes and to learn more about text processing (that is a wonderful surprise for a neurolinguist like myself!). All the best!

Vania de Aguiar

Who will you learn with?

Ian Witten

I grew up in Ireland, studied at Cambridge, and taught computer science at the Universities of Essex in England and Calgary in Canada before moving to paradise (aka New Zealand) 25 years ago.

Who developed the course?

Sitting among the top 3% of universities world-wide, The University of Waikato prepares students to think critically and to show initiative in their learning.

What’s the difference between a free course and an upgraded course?

Free:

  • Access to the course for its duration + 14 days, regardless of when you join (this includes access to articles, videos, peer review steps, quizzes)
  • No access to course tests
  • No certificate

Upgraded:

  • Unlimited access to the course, for as long as it exists on FutureLearn (this includes access to articles, videos, peer review steps, quizzes)
  • Access to course tests
  • A Certificate of Achievement when you complete the course

Find out more

Get extra benefits, upgrade this course. For $84 (+ shipping) you'll get:

Unlimited access

Upgrading will mean you get unlimited access to the course.

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  • Take the course at your own pace
  • Refer to the material at any point in future

If you’re taking a course for free you have access to the course for its duration + 14 days, regardless of when you join. If you upgrade the course you have access for as long as the course exists on FutureLearn.

Access to tests

When you upgrade you’ll have access to any tests during the course.

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  • Validate your learning
  • Ensure you have mastered the material
  • Qualify for a certificate

To receive a Certificate of Achievement you need to take any tests and score over 70%. You don’t get access to tests if you choose to take a course for free.

Certificate of Achievement

Upgrading means you’ll receive a Certificate of Achievement when you complete the course.

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  • Prove your success when applying for jobs or courses
  • Celebrate your hard work
  • Display on your LinkedIn or CV

To receive a Certificate of Achievement you need to mark 90% of the steps on the course as complete, and score over 70% on any course tests.

Upgrade


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