**Apologies for cross posting**
The latest virtual training series from the National Information Standards Organization covers text and data mining. Join us and take your research and analytics to the next level by mastering these critical skills!
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
A solid understanding of text and data mining concepts,
Proficiency in using Python for text and data mining tasks
Ability to apply text and data mining skills to real-world library applications and case studies
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. Discount 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, sign up 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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