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DTSTART;TZID=America/New_York:20231117T100000
DTEND;TZID=America/New_York:20231119T130000
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SUMMARY:2023 Winter School: Exploring Python for Data Analysis and Machine Learning in the Humanities
DESCRIPTION:Note: Workshop is 6 hours and will be conducted over 2 days (17th & 19th November 2023\; 10AM to 1PM ET) with each session of 3 hours per day on specific topics as below:Session 1: Introduction to Python (1 Hour)Session 2: Working with Data in Python (1.5 Hours)Session 3: Visualizing Humanities Data in Python (1.5 Hours)Session 4: Intro to Machine Learning in Python (1 Hour)Session 5: Hands-on Machine Learning Project (1 Hour)Session 6: Q&A and Next Steps (0.5 Hour)Target Audience: Beginners and novices interested in data analysis\, data visualization\, and machine learning using Python\, particularly in the context of humanities data.Duration: 6 hours of active instruction (spread over multiple sessions) with 15 hours of break time.Instructor: Daniel Agbaji is a seasoned researcher\, software developer\, and data scientist from Nigeria. He earned his Master of Science (MSc.) and Master of Library and Information Science (MLS) degrees from Emporia State University\, Kansas\, USA\, and currently studying to earn his doctorate at the University of North Texas (UNT). His research area is applied artificial intelligence\, machine learning\, software development\, data science\, information science\, and emerging technologies. He teaches the data analysis and knowledge discovery course to the master's students at UNT. He is passionate about empowering others to learn relevant data science skills.
X-ALT-DESC;FMTTYPE=text/html:Note: Workshop is 6 hours and will be conducted over 2 days (17th &\; 19th November 2023\; 10AM to 1PM ET) with each session of 3 hours per day on specific topics as below:
Session 1: Introduction to Python (1 Hour)
Session 2: Working with Data in Python (1.5 Hours)
Session 3: Visualizing Humanities Data in Python (1.5 Hours)
Session 4: Intro to Machine Learning in Python (1 Hour)
Session 5: Hands-on Machine Learning Project (1 Hour)
Session 6: Q&\;A and Next Steps (0.5 Hour)
Target Audience: Beginners and novices interested in data analysis\, data visualization\, and machine learning using Python\, particularly in the context of humanities data.
Duration: 6 hours of active instruction (spread over multiple sessions) with 15 hours of break time.
Instructor: Daniel Agbaji is a seasoned researcher\, software developer\, and data scientist from Nigeria. He earned his Master of Science (MSc.) and Master of Library and Information Science (MLS) degrees from Emporia State University\, Kansas\, USA\, and currently studying to earn his doctorate at the University of North Texas (UNT). His research area is applied artificial intelligence\, machine learning\, software development\, data science\, information science\, and emerging technologies. He teaches the data analysis and knowledge discovery course to the master&rsquo\;s students at UNT. He is passionate about empowering others to learn relevant data science skills.
LOCATION:
UID:e.1224.868391
SEQUENCE:3
DTSTAMP:20260405T075612Z
URL:https://www2.asist.org/events/Details/2023-winter-school-exploring-python-for-data-analysis-and-machine-learning-in-the-humanities-971384?sourceTypeId=Hub
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