Practical Data Mining
University of Waikato via FutureLearn Program
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22
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Overview
This flexible program of online courses is aimed at anyone who deals in data and is seriously concerned about obtaining information from it.
You’ll begin with a practical introduction to data mining and learn to mine your own data using the popular Weka workbench. You’ll go on to discover more advanced data mining techniques, including how to mine large datasets.
Finally, you’ll look at a variety of popular packages that can be used to extend Weka’s functionality, and gain the skills you need to become a data mining wizard.
Syllabus
Courses under this program:
Course 1: Data Mining with Weka
-Discover practical data mining and learn to mine your own data using the popular Weka workbench.
Course 2: More Data Mining with Weka
-Learn more about practical data mining, including how to deal with large data sets. Use advanced techniques to mine your own data.
Course 3: 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!
Courses
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5 weeks long, 3 hours a week
View detailsLearn how to mine your own data
Today’s world generates more data than ever before! Being able to turn it into useful information is a key skill. This course introduces you to practical data mining using the Weka workbench. We’ll dispel the mystery that surrounds the subject. We’ll explain the principles of popular algorithms. We’ll show you how to use them in practical applications. You’ll get plenty of experience actually mining data during the course, and afterwards you’ll be well equipped to mine your own. Weka originated at the University of Waikato in NZ, and Ian Witten has authored a leading book on data mining.
This course is aimed at anyone who deals in data. It involves no computer programming, although you need some experience with using computers for everyday tasks. High school maths should be more than enough and you’ll need an understanding of some elementary statistics concepts (means and variances).
You will download the free Weka software during Week 1. 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.)
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5 weeks long, 4 hours a week
View detailsLearn how to process, analyse, and model large data sets
On this course, led by the University of Waikato where Weka originated, you’ll be introduced to advanced data mining techniques and skills.
Following on from their first Data Mining with Weka course, you’ll now be supported to process a dataset with 10 million instances and mine a 250,000-word text dataset.
You’ll analyse a supermarket dataset representing 5000 shopping baskets and learn about filters for preprocessing data, selecting attributes, classification, clustering, association rules, cost-sensitive evaluation.
You’ll also explore learning curves and how to automatically optimize learning parameters.
This course is aimed at anyone who deals in data professionally or is interested in furthering their professional or academic skills in data science.
This course follows on from Data Mining with Weka and it’s recommended that you complete that course first unless you already have a rudimentary knowledge of Weka.
As with the previous course, it involves no computer programming, although you need some experience with using computers for everyday tasks.
High school maths is more than enough; some elementary statistics concepts (means and variances) are assumed.
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.)
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5 weeks long, 4 hours a week
View detailsExtend 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.
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.
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.)
Taught by
Ian Witten
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