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New Short Course for Forensic Practitioners Introduces Machine Learning Algorithms

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The Center for Statistics and Applications in Forensic Evidence (CSAFE) is hosting a three-session short course for forensic practitioners interested in learning the basics of machine learning. The online course meets 1–3 p.m. CT on Sept. 1, Sept. 8 and Sept. 15.

The short course, Machine Learning for Forensic Practitioners, will provide an overview of machine learning and how it applies to forensic evidence. Attendees will learn the basics of supervised learning algorithms in the context of forensic applications, including classification trees, random forests and neural networks. The sessions will explore the limitations of machine learning algorithms and methods for assessing their performance.

The sessions will be co-led by Heike Hofmann, a professor of statistics and professor-in-charge of the Data Science Program at Iowa State University; Alicia Carriquiry, CSAFE director and a Distinguished Professor and President’s Chair of Statistics at Iowa State University; and Jeff Salyards, a research scientist at CSAFE.

Each session will build upon the previous ones, and the recordings will be available if registrants cannot attend one of the live sessions.

“This machine learning course is a great kickoff to the many new additions to our learning opportunities debuting in the coming year,” said Anthony Greiter, the learning and development specialist at CSAFE.

CSAFE also will be offering the Statistical Thinking for Forensic Practitioners Short Course on Oct. 14, Oct. 21, Oct. 28 and Nov. 4 from 10 a.m.–noon CT. This introductory course covers fundamental concepts from probability and statistics motivated by forensic issues, followed by a detailed investigation of how they are used to assess forensic evidence’s probative value.

Hal Stern, CSAFE co-director and Provost and Executive Vice Chancellor and Chancellor’s Professor of Statistics at the University of California, Irvine, will teach all four sessions.

Both short courses are free, but registration is required. For more information and to register, visit