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<ul class="nav navbar-nav">
<li>
<a href="index.html">Home</a>
</li>
<li>
<a href="code_of_conduct.html">Code of Conduct</a>
</li>
<li>
<a href="evaluation.html">Evaluation</a>
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<li>
<a href="syllabus.html">Syllabus</a>
</li>
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<a href="schedule.html">Schedule</a>
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<h1 class="title toc-ignore"><strong>Syllabus</strong></h1>
</div>
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<p><br></p>
<div id="course-description" class="section level3">
<h3>Course Description</h3>
<p>This course is focused on helping students learn how to apply their
data science knowledge in non-academic settings. Students will partner
with <a
href="https://source.jhu.edu/about/partner-organizations">community-based
organizations (CBOs)</a> in Baltimore to work on a data science related
goal. Students will focus on developing critical service-learning and
professional skills as they work with CBOs to accomplish a data science
related goal. <em>This course can feel uncomfortable: students are
expected to be self motivated and work on solutions to problems without
being told what to do.</em> While difficult, experiencing this kind of
uncertainty is similar to working as a data scientist in academic
settings or industry.</p>
<p><br></p>
</div>
<div id="important-links" class="section level3">
<h3>Important Links</h3>
<ul>
<li><strong>Class Website:</strong> <a
href="https://jhudatascience.org/Baltimore_Community_Course"
class="uri">https://jhudatascience.org/Baltimore_Community_Course</a></li>
<li><strong>Zoom link</strong>: Instructors will send to registered
students</li>
<li><strong>Slack Workspace</strong>: Instructors will send to
registered students</li>
</ul>
<p><br></p>
</div>
<div id="logistics" class="section level3">
<h3>Logistics</h3>
<ul>
<li><strong>Class Sessions:</strong>
<ul>
<li>The course will meet <strong>Friday 1:30 - 2:50pm ET</strong> during
<strong>1st and 2nd terms</strong>.</li>
<li>Students who take the class must commit to <strong>both</strong>
terms for project continuity.</li>
<li>Each term is worth 1.5 credit hours (3 total).</li>
<li><a
href="https://www.jhsph.edu/courses/course/38607/2023/140.801.01/baltimore-community-data-science">Part
I dates</a>: Monday, August 28 - Monday, October 23</li>
<li><a
href="https://www.jhsph.edu/courses/course/38608/2023/140.802.01/baltimore-community-data-science-ii">Part
II dates</a>: Wednesday, October 25 - Friday, December 22</li>
</ul></li>
<li><strong>Location:</strong>
<ul>
<li>Students will meet in class (virtually) once per week.</li>
<li>Students will work in groups outside of class on community-based
projects virtually on Zoom.</li>
</ul></li>
<li><strong>CBO Meetings:</strong>
<ul>
<li>This depends on the project goals, but students are expected to meet
with CBO leadership for approximately 30 min - 1 hr every 2 weeks for
the duration of the terms.</li>
<li>Meetings will also be supplemented by emails.</li>
<li>Keep in mind that CBO members are busy and staff may not be getting
paid for this work.</li>
</ul></li>
<li><strong>Communication:</strong>
<ul>
<li>Instructors and students will communicate through Slack.</li>
<li>Instructors will email you about how to connect to Slack.</li>
</ul></li>
</ul>
<p><br></p>
</div>
<div id="instructors" class="section level3">
<h3>Instructors</h3>
<ul>
<li><a href="https://carriewright11.github.io/">Carrie Wright</a> (<a
href="mailto:cwrigh60@jhu.edu">cwrigh60@jhu.edu</a>)</li>
<li><a href="https://www.avahoffman.com/">Ava Hoffman</a> (<a
href="mailto:ava.hoffman@jhu.edu">ava.hoffman@jhu.edu</a>)</li>
<li><a href="https://mrosenblumbiostat.wordpress.com/">Michael
Rosenblum</a> (<a href="mailto:mrosen@jhu.edu">mrosen@jhu.edu</a>)</li>
</ul>
<p><br></p>
</div>
<div id="requirements" class="section level3">
<h3>Requirements</h3>
<ul>
<li>Students are required to have some prior experience with R
programming (or other languages) and need to have taken the following
data science courses (or have equivalent experience):
<ul>
<li>140.711 Advanced Data Science I and 140.712 Advanced Data Science
II</li>
</ul></li>
<li>Instructor permission is required to enroll in the course.</li>
</ul>
<p><br></p>
</div>
<div id="schedule-and-materials" class="section level3">
<h3>Schedule and Materials</h3>
<p>Please see the <a href="schedule.html">Schedule</a> tab.</p>
<p><br></p>
</div>
<div id="expectations-of-students" class="section level3">
<h3>Expectations of Students</h3>
<p>Students will work with CBO partners as a team (3-5) for the
following deliverables:</p>
<ul>
<li>Learn about the partner CBO, the goals of the CBO, and how data may
be helpful for these goals</li>
<li>Discuss the data needs of the create a plan to work with the
CBO</li>
<li>Create a data science product that aligns with the goals of the
CBO</li>
<li>Create an implementation plan and training for the CBO</li>
<li>Create a sustainability plan for the CBO to work with and continue
to maintain the data science product respectively including narratives
(“story”) about the data product - what it means, the limitations
etc.</li>
<li>Additional possible training and thoughts for CBO partners on
further future data-related initiatives</li>
</ul>
<p>In addition to working on data science projects, students are also
expected to individually hone their critical service-learning skills and
professional skills. This involves participating in written exercises
and discussions, as well as active work to stay organized and maintain
communication with teammates and the CBO.</p>
<p>See the <a
href="https://jhudatascience.org/Baltimore_Community_Course/projects.html">project
page</a> for more information about project guidelines.</p>
<p><br></p>
</div>
<div id="expectations-of-cbos" class="section level3">
<h3>Expectations of CBOs</h3>
<p>Partners will need to provide students with details on the project
goals and uses, access to relevant data (could be de-identified or
simulated if privacy is an issue), feedback about whether their goals
are being met, and time and willingness to learn about how to use and
possibly maintain the data product that the students work with them to
create.</p>
<p><br></p>
</div>
<div id="student-learning-objectives" class="section level3">
<h3>Student Learning Objectives</h3>
<p>Students who complete the course will be able to:</p>
<ol style="list-style-type: decimal">
<li>Describe the history of Johns Hopkins and the biostatistics
department in the Baltimore community. Evaluate and discuss how this
<strong>historical context</strong> and the <strong>current
context</strong> influences our interactions with community
members.</li>
<li><strong>Critically reflect</strong> on their own service-learning
project work and how their role as a statistician impacts the CBO, as
well as the greater context of society and social structures (not just
the course project).</li>
<li>Articulate what <strong>critical service-learning</strong> is and
describe how it differs from traditional community service endeavors.
Evaluate and discuss how other methods can cause harm to
communities.</li>
<li>Understand more about how to successfully <strong>navigate
challenges</strong> that occur when applying data cleaning, wrangling,
analysis, collection planning, visualization, and communication skills
to problems in <strong>non-academic settings</strong>, as the students
<strong>create</strong> (with the guidance and help of the CBO)
<strong>data science products</strong> for the goals of the assigned CBO
project.</li>
<li>Work with others to <strong>create an implementation plan</strong>
for the data science products that is viable and useful for the
respective CBO members. Work with stakeholders at a high level to
understand their needs as well as the limitations of the data.</li>
<li>Use teaching methods to <strong>teach others</strong> from various
backgrounds and experiences to use data science techniques to work with
data and communicate effectively about data.</li>
<li>Plan for CBO to continue to work with data science products in a
<strong>sustainable way</strong> even after projects are over.</li>
</ol>
<p><br></p>
</div>
<div id="grading" class="section level3">
<h3>Grading</h3>
<p>Please see the <a href="evaluation.html">Evaluation</a> tab.</p>
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