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<span style="font-size: 11pt; font-family: Calibri, sans-serif; border: 1pt none windowtext; padding: 0in; color: rgb(36, 36, 36);" class="ContentPasted0">The
<a href="https://www.nnlm.gov/about/centers/ncds" title="https://www.nnlm.gov/about/centers/ncds" data-loopstyle="linkonly" id="LPNoLPOWALinkPreview_1">
NNLM National Center for Data Services</a> is excited to announce a new class they’ve developed, the <a href="https://www.nnlm.gov/training/class/fundamentals-health-data-science" data-auth="NotApplicable" data-linkindex="2" class="ContentPasted0" data-loopstyle="linkonly"><i><span style="color: rgb(5, 99, 193);">Fundamentals
of Health Data Science</span></i></a>, which will run for the first time this fall! This is a mostly asynchronous 9-week course (Sept. 5 – Nov. 3) designed to improve knowledge and skills in data science, enabling learners to add or enhance data science training
and services at their institutions.</span><span style="font-size: 11pt; font-family: Calibri, sans-serif; color: rgb(36, 36, 36);"><o:p class="ContentPasted0"> </o:p></span></p>
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<span><span style="font-size: 11pt; font-family: Calibri, sans-serif; border: 1pt none windowtext; padding: 0in; color: rgb(36, 36, 36);" class="ContentPasted0">This course is structured to provide learners with an opportunity to interact with each other, with
course facilitators, and with community experts in library data science work. The goal is to help build up confidence in discussing data science issues and help connect the growing community of information professionals with expertise in this area.</span></span><span style="font-size: 11pt; font-family: Calibri, sans-serif; color: rgb(36, 36, 36);"><o:p class="ContentPasted0"> </o:p></span></p>
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<span><span style="font-size: 11pt; font-family: Calibri, sans-serif; border: 1pt none windowtext; padding: 0in; color: rgb(36, 36, 36);" class="ContentPasted0">Throughout this course, learners will read foundational texts, discuss topics in data science, complete
assignments that will help grow their understanding, and analyze a health science dataset. The course will focus on using Python in Google Colaboratory to work with data, including importing, inspecting, cleaning, and analyzing datasets, as well as making
visualizations.</span></span><span style="font-size: 11pt; font-family: Calibri, sans-serif; color: rgb(36, 36, 36);"><o:p class="ContentPasted0"> </o:p></span></p>
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<span><span style="font-size: 11pt; font-family: Calibri, sans-serif; border: 1pt none windowtext; padding: 0in; color: rgb(36, 36, 36);" class="ContentPasted0">If you are interested in applying for this course as either a <b class="ContentPasted0">learner</b> or
a <b class="ContentPasted0">community expert</b>, please see the <a href="https://www.nnlm.gov/training/class/fundamentals-health-data-science" data-auth="NotApplicable" data-linkindex="3" class="ContentPasted0" data-loopstyle="linkonly"><span style="color: rgb(5, 99, 193);">course
page</span></a> for additional information and application details. Please submit the form(s) by Sunday, July 30, 2023 at 8:59 p.m. Pacific Time.</span></span><span style="font-size: 11pt; font-family: Calibri, sans-serif; color: rgb(36, 36, 36);"><o:p class="ContentPasted0"> </o:p></span></p>
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<p class="MsoNormal"><b>Emily Hamstra, MSI </b>(she/her) | Assistant Director<o:p></o:p></p>
<p class="MsoNormal">Network of the National Library of Medicine, Region 5<o:p></o:p></p>
<p class="MsoNormal">University of Washington Box 357155<o:p></o:p></p>
<p class="MsoNormal">Seattle, WA 98195<o:p></o:p></p>
<p class="MsoNormal"><a href="https://nnlm.gov/">https://nnlm.gov</a> | <a href="mailto:ehamstra@uw.edu">
ehamstra@uw.edu</a> <o:p></o:p></p>
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