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DTSTART;TZID=America/New_York:20261203T160000
DTEND;TZID=America/New_York:20261203T170000
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SUMMARY:HECA College Knowledge Major Talks: Data Science
DESCRIPTION:Join us for a Major Talks webinar as we learn from data science specialist Swami Swaminathan\, who will explore key factors to consider when guiding prospective data science students. Gain valuable insights from representatives Dr. Jeff Phillips of the University of Utah and Dr. Li Han from Clark University as they highlight the distinctive strengths of their data science programs and introduce compelling alternative majors. Don't miss this opportunity to deepen your expertise and better support your students' academic journeys!University of Utah - Learn about the University of Utah's BS in Data Science\, which launched in 2019.  It offers a wide variety of technically deep courses\, requires at least 3 courses in some data rich domain outside of CS and Math\, and has a dedicated Ethics of Data Science course.  Clark University - Explore how Clark University's interdisciplinary Data Science Program combines common foundations\, core data science theories and methods\, and domain-specific knowledge. The presentation will highlight the program's flexible curriculum\, experiential learning opportunities\, and preparation for diverse careers.Dr. Jeff Phillips\nProfessor\nUniversity of Utah\nJeff M. Phillips is a Professor in the Kahlert School of Computing.  He also directs the Utah Center for Data Science as well as the Data Science Program. He research specializes in Geometric Data Analysis and Algorithms for Big Data\, with an underlying goal to understand data science in the age of AI.Dr. Li Han\nDirector of Data Science and Professor of Computer Science\nClark UniversityDr. Li Han is a Professor of Computer Science and Director of the Interdisciplinary Data Science Program at Clark University in Worcester\, MA. Her teaching and research span data science\, machine learning\, and interdisciplinary collaborations addressing real-world questions in a wide range of fields. She has extensive experience mentoring undergraduate and graduate students. She also leads CROSSROADS\, an NSF-funded project that develops a holistic approach to data science education and expands opportunities for hands-on\, interdisciplinary learning.Click here to register\nFor those who are unable to attend\, we will have a recorded video available for viewing from the HECA Info Hub.
X-ALT-DESC;FMTTYPE=text/html:<!DOCTYPE html><html><head><title></title></head><body aria-disabled="false"><p><span style="white-space: pre-line\; caret-color: rgb(35\, 35\, 51)\; color: rgb(0\, 0\, 0)\; font-family: Verdana\, Geneva\, sans-serif\; font-size: 14px\; letter-spacing: 0.42px\; background-color: rgb(255\, 255\, 255)\;">Join us for a Major Talks webinar as we learn from data science specialist Swami Swaminathan\, who will explore key factors to consider when guiding prospective data science students. Gain valuable insights from representatives Dr. Jeff Phillips of the University of Utah and Dr. Li Han from Clark University as they highlight the distinctive strengths of their data science programs and introduce compelling alternative majors. Don&rsquo\;t miss this opportunity to deepen your expertise and better support your students&rsquo\; academic journeys!</span></p><p><span style="color: rgb(0\, 0\, 0)\;"><span style="font-size: 14px\;"><span style="font-family: Verdana\,Geneva\,sans-serif\;"><strong fr-original-style="" style="font-weight: 700\;">University of Utah - </strong>Learn about the University of Utah&#39\;s BS in Data Science\, which launched in 2019. &nbsp\;It offers a wide variety of technically deep courses\, requires at least 3 courses in some data rich domain outside of CS and Math\, and has a dedicated Ethics of Data Science course. &nbsp\;</span></span></span></p><p><span style="color: rgb(0\, 0\, 0)\;"><span style="font-size: 14px\;"><span style="font-family: Verdana\, Geneva\, sans-serif\;"><strong fr-original-style="" style="font-weight: 700\;">Clark University -</strong> Explore how Clark University&#39\;s interdisciplinary Data Science Program combines common foundations\, core data science theories and methods\, and domain-specific knowledge. The presentation will highlight the program&#39\;s flexible curriculum\, experiential learning opportunities\, and preparation for diverse careers.</span></span></span></p><p><img src="https://res.cloudinary.com/micronetonline/image/upload/v1793022176/tenants/93bb562b-fafd-4234-86f4-411a45401199/2fd283c4552041b8975ceacc44e2bc31/jeffp-small-Jeff-Phillips.jpg" style="width: 200px\; height: 270px\; position: relative\; max-width: 100%\; cursor: pointer\; padding: 0px 1px\;" width="200" height="270" fr-original-style="width: 200px\; height: 270px\;" fr-original-class="fr-draggable" /></p><p><font color="#0a505e"><span style="font-size: 14px\;"><strong fr-original-style="" style="font-weight: 700\;"><em><span style="font-family: Verdana\,Geneva\,sans-serif\;">Dr. Jeff Phillips</span></em></strong></span></font><br /><span style='caret-color: rgb(0\, 0\, 0)\; color: rgb(51\, 51\, 51)\; font-family: "Open Sans"\; font-size: 11px\; font-weight: bold\;'><span style="font-family: Verdana\,Geneva\,sans-serif\;"><font color="#0A505E">Professor</font></span></span><br /><span style='caret-color: rgb(0\, 0\, 0)\; color: rgb(51\, 51\, 51)\; font-family: "Open Sans"\; font-size: 11px\; font-weight: bold\;'><span style="font-family: Verdana\,Geneva\,sans-serif\;"><font color="#0A505E">University of Utah</font></span></span><span style='caret-color: rgb(0\, 0\, 0)\; color: rgb(51\, 51\, 51)\; font-family: "Open Sans"\; font-size: 12px\; font-weight: bold\;'><span style="font-family: Verdana\,Geneva\,sans-serif\;"><em><font color="#0A505E"><br /></font></em></span></span></p><p><span style="font-family: Verdana\, Geneva\, sans-serif\; font-size: 14px\;"><em><span style="color: rgb(0\, 0\, 0)\;">Jeff M. Phillips is a Professor in the Kahlert School of Computing. &nbsp\;He also directs the Utah Center for Data Science as well as the Data Science Program. He research specializes in Geometric Data Analysis and Algorithms for Big Data\, with an underlying goal to understand data science in the age of AI.</span></em></span></p><p><img src="https://res.cloudinary.com/micronetonline/image/upload/v1793022167/tenants/93bb562b-fafd-4234-86f4-411a45401199/6f387bb9d7f643379599d8bc0b5159a5/Li-Han-Portrait-L-Han.jpg" style="width: 210px\; position: relative\; max-width: 100%\; cursor: pointer\; padding: 0px 1px\;" width="210" height="263" fr-original-style="width: 210px\;" fr-original-class="fr-draggable" /></p><p><font color="#0a505e"><span style="font-size: 14px\;"><strong fr-original-style="" style="font-weight: 700\;"><em><span style="font-family: Verdana\,Geneva\,sans-serif\;">Dr. Li Han</span></em></strong></span></font><br /><font color="#0a505e"><span style="font-size: 11px\;"><strong fr-original-style="" style="font-weight: 700\;"><span style="font-family: Verdana\, Geneva\, sans-serif\;">Director of Data Science and Professor of Computer Science</span></strong></span></font><br /><font color="#0a505e"><span style="font-size: 11px\;"><strong fr-original-style="" style="font-weight: 700\;"><span style="font-family: Verdana\, Geneva\, sans-serif\;"><font color="#0a505e"><span style="font-size: 11px\;"><strong fr-original-style="" style="font-weight: 700\;"><em><span style="font-family: Verdana\, Geneva\, sans-serif\;">Clark University</span></em></strong></span></font></span></strong></span></font></p><p><span style="font-family: Verdana\, Geneva\, sans-serif\; font-size: 14px\;"><em><span style="color: rgb(0\, 0\, 0)\;">Dr. Li Han is a Professor of Computer Science and Director of the Interdisciplinary Data Science Program at Clark University in Worcester\, MA. Her teaching and research span data science\, machine learning\, and interdisciplinary collaborations addressing real-world questions in a wide range of fields. She has extensive experience mentoring undergraduate and graduate students. She also leads CROSSROADS\, an NSF-funded project that develops a holistic approach to data science education and expands opportunities for hands-on\, interdisciplinary learning.</span></em></span></p><hr style="caret-color: rgb(51\, 51\, 51)\; color: rgb(51\, 51\, 51)\; font-family: &quot\;Open Sans&quot\;\; font-size: 16px\; clear: both\; -webkit-user-select: none\; break-after: page\;" fr-original-style="caret-color: rgb(51\, 51\, 51)\; color: rgb(51\, 51\, 51)\; font-family: &quot\;Open Sans&quot\;\; font-size: 16px\;" /><div style='caret-color: rgb(51\, 51\, 51)\; color: rgb(51\, 51\, 51)\; font-family: "Open Sans"\; font-size: 16px\; line-height: 18px\;'><p style="text-align: center\;"><span style="font-family: Verdana\, Geneva\, sans-serif\; font-size: 12px\;"><span style="font-family: Verdana\, Geneva\, sans-serif\; font-size: 18px\;"><strong fr-original-style="" style="font-weight: 700\;"><span style="color: rgb(10\, 80\, 94)\;">Click</span></strong><strong fr-original-style="" style="font-weight: 700\;">&nbsp\;</strong></span></span><a fr-original-style="" href="https://us02web.zoom.us/webinar/register/WN_kgtNKTbxQwa4g70Ip4vbGw" rel="noopener noreferrer" style="-webkit-user-select: auto\;" target="_blank"><span style="font-family: Verdana\, Geneva\, sans-serif\; font-size: 12px\;"><span style="font-size: 18px\;"><strong fr-original-style="" style="font-weight: 700\;"><span style="color: rgb(118\, 184\, 191)\;"><span style="font-family: Verdana\, Geneva\, sans-serif\;">here</span></span></strong></span></span></a><span style="font-family: Verdana\, Geneva\, sans-serif\; font-size: 12px\;"><span style="font-family: Verdana\, Geneva\, sans-serif\; font-size: 18px\;"><strong fr-original-style="" style="font-weight: 700\;">&nbsp\;</strong><strong fr-original-style="" style="font-weight: 700\;"><span style="color: rgb(10\, 80\, 94)\;">to register</span></strong></span><br /><em>For those who are unable to attend\, we will have a recorded video available for viewing from the HECA Info Hub.</em></span></p></div></body></html>
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DTSTAMP:20261027T155004Z
URL:https://association.hecalive.org/heca-master-calendar/Details/heca-college-knowledge-major-talks-data-science-1974195?sourceTypeId=Hub
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