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Advanced Data Mining with Weka

Ian Witten, Peter Reutemann, Jemma König, Eibe Frank, and Mark Hall

Most FutureLearn courses run multiple times. Every run of a course has a set start date but you can join it and work through it after it starts. Find out more 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. You can use the hashtag #FLadvanceddatamining to talk about this course on social media.

Topics Covered

Time series analysis
Data stream mining
Incremental classifiers
Evolving data streams
Support vector machines
Accessing data mining in R
Distributed data mining
Map-reduce framework
Scripting data mining in Python and Groovy
Applications: Soil analysis, Sentiment analysis, Bioinformatics, MRI neuroimaging, Image classification

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Reviews summary

Mastering advanced weka & data mining

According to students, this is a largely positive course that provides a deep dive into advanced data mining concepts using Weka. Learners particularly highlight the practical applications and hands-on examples, finding the Python scripting integration highly useful for real-world scenarios. While the course delivers solid and current content, especially in areas like time series and data stream analysis, some find the pace very fast and feel it assumes extensive prior knowledge beyond the stated prerequisites. The R and Groovy sections receive mixed feedback, with some wishing for more depth. Overall, it's highly recommended for experienced Weka users seeking to advance their skills.

Python scripting is praised, but R and Groovy sections are less developed.

"The Python scripting parts were a great bonus, making it practical and a good addition."

"Specifically, the R and Groovy sections felt tacked on and rushed, lacking the depth of other modules."

"I had hoped for more in-depth coding examples, especially for the more complex aspects presented in the course."

Content and tools are generally current, with updates noted.

"My only minor gripe is that some of the Weka interfaces shown in the videos seemed slightly outdated compared to the latest version, but it wasn't a major hindrance."

"A minor point: some of the older reviews mention outdated interfaces, but I didn't experience that significantly in the current run."

"I found the course material to be current and the examples relevant to real-world scenarios."

Emphasizes real-world applications and hands-on learning.

"The practical applications covered, like sentiment analysis, were very well illustrated."

"I appreciated the hands-on examples, though sometimes the pace was a bit too fast for me to grasp everything without re-watching."

"I can immediately apply these skills to my work, which is invaluable."

Provides deep insights into complex data mining techniques.

"The course content is highly relevant for anyone looking to deepen their understanding of data mining, especially with Weka."

"This course truly pushes me beyond basic Weka usage. I've been using Weka for years, and this still taught me new, valuable techniques."

"I found the content solid, though it demanded a strong prior understanding of Weka and data mining concepts."

The course can be fast-paced and demands strong prior knowledge.

"While the topics covered are advanced, I felt some parts of the course assumed too much prior knowledge beyond the stated prerequisites."

"The pace was too fast, and the explanations were insufficient for the 'advanced' nature of the topics. I found myself constantly looking for external resources."

"I completed the 'More Data Mining with Weka' course and still felt overwhelmed by some of the content."

Career center

Learners who complete Advanced Data Mining with Weka will develop knowledge and skills that may be useful to these careers:

Reading list

We've selected 50 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Advanced Data Mining with Weka.

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Advanced Data Mining with Weka

Topics Covered

Topics Covered

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Reviews summary

Mastering advanced weka & data mining

Career center

Reading list

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