**Apologies for cross posting**


October’s training series from the National Information Standards Organization introduces participants to text and data mining, and the deadline for early bird registration rates is September 28!  Register now and take advantage of this timely professional development opportunity. 


Text and Data Mining | Online Training Series

Thursdays, 11:00 am–12:30 pm EDT (US/Canada)

October 12–December 7, 2023


This virtual training series will equip students with the essential skills and knowledge required to undertake text and data mining tasks. The comprehensive course will introduce participants to key concepts and tools of text and data mining, including data types, data structures, data pre-processing, text processing, data mining techniques, text mining techniques, and advanced topics in both data and text mining. Each session will include a Python component, discussing the importance of Python and its libraries in handling various aspects of text and data mining. 


Previous knowledge of Python is not required. By the end of the course, participants will demonstrate 



Event Sessions


The series consists of eight weekly segments, each lasting 90 minutes. Specific dates are October 12, 19, and 26 and 25; November 2, 9, and 16; and December 7.


Training Facilitator: William Mattingly, Postdoctoral Fellow, Smithsonian Institution’s Data Science Lab


See the NISO website for more information and to register. Discounts are available for NISO Voting Members/LSA Members. Early bird registration deadline is Thursday, September 28, 2023. Recordings will be available for those who cannot attend the live broadcast(s). Please note that it is not possible to register for individual program segments or lectures.


We hope you’ll take advantage of this unique professional development opportunity. And remember, join us by September 28 to take advantage of early bird registration rates!


Best, 


The NISO Team


NISO

3600 Clipper Mill Road, Suite 302

Baltimore, MD 21211

Phone: 301.654.2512

E-mail: [log in to unmask]



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