Advanced Data Mining

Find the useful information hidden in your data! This course surveys comput­er-intensive methods for inductive classification and estimation, drawn from statistics, machine learning, and data mining. Instructor John Elder will describe the key in­ner workings of leading algorithms, compare their merits, and briefly demon­strate their relative effectiveness on practical applications.

Classical statistical techniques, both linear and nonparametric, will be reviewed and then the ways in which these basic tools are modified and combined into powerful modern methods will be outlined. The course emphasizes practical advice and focuses on the essential techniques of resampling, visualization, and ensembles. Actual scientific and business examples will illustrate proven techniques employed by expert analysts. Along the way, relative strengths and distinctive properties of the leading commercial software products for data mining will be discussed.

This intensive short course provides a broad overview, drawing connections between major devel­opments in the diverse fields that contribute to predictive analytics, in­cluding cutting-edge ways to mine text and graphical networks. Previous partici­pants have found this "big picture" to be very useful for identifying techniques to use immediately, as well as approaches wor­thy of further exploration, for research or practical problem-solving.

Intended audience

Those who work with data and wish to understand and use recent develop­ments in predictive analytics. At the conclusion of this course, you should be able to discern the basic strengths of competing methods and select the ap­propriate tools for your applications.

Course fee

The course fee is $1,000 per person and includes a complimentary copy of The Handbook of Statistical Analysis and Data Mining.


"Dr. Elder provided examples shedding light on complex concepts. He gave the big picture all along the way."

"Gave real practical insights from a practitioner's point of view."

"Finally someone told me how things are done, not just how great data mining is."

"Most valuable were the insights into the essence of various methods, their relative strengths and weaknesses, and the important open research areas."

"Very interesting, knowledgeable, and entertaining approach."


Dr. John Elder founded Elder Research, America’s largest and most experienced analytics consultancy in 1995. With offices in Charlottesville, VA, Baltimore, MD, Raleigh, NC, and Washington, DC, they’ve solved hundreds of challenges for commercial and government clients by extracting actionable knowledge from all types of data. Dr. Elder co-authored three books—on practical data mining, ensembles, and text mining—two of which won “book of the year” awards. John has created data mining tools, was a discoverer of ensemble methods, chairs international conferences, and is a popular workshop and keynote speaker.