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Graduate Certificate
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Mary Lou Fulton Teachers College
Advanced Analytics in Higher Education
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The graduate certificate in Advanced Analytics in Higher Education
prepares professionals to conduct the advanced analytics needed to
support data-driven decision making in all academic and operational areas
of higher and postsecondary education.
In this online certificate program, the coursework addresses the
application of data mining, predictive analytics, sentiment analysis, and
data visualization techniques to higher education-specific problems with
the goal of preparing individuals at all levels to use data in their decision-
making processes. Through real-world projects using top tools such as
Tableau and RapidMiner, students apply the knowledge and skills learned
while gaining an understanding of the security and ethical considerations
of analytics.

2. Program Courses
HED 605: Data Management & Preparation for Higher Education Analytics
HED 603: Foundation of Data Analytics in Higher Education
HED 604: Analytics Process & Technology in Higher Education
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How are decisions made in university management? How do institutions use data
analytics to inform their decisions? How can we improve the use of data analytics
in decision-making? This course aims to provide participants with insights into the
functioning of data analytics in decision-making at higher education institutions by
exposing them to theoretical explanations of decision-making as well as various
examples of data and analytics that support different spectrums of administration.
A successful analytic project requires a repeatable, documentable process that uses
the right technology for the institution’s question. This course teaches the student how
to properly define a question, identify the appropriate types of analytic tools for the
question, and teaches a repeatable, industry-standard process for managing an analytic
project. It further explains why it is important to keep documentation on each step and
best-practice techniques for doing so.
Data-informed decision-making only works if the right data is used, prepared correctly,
and managed carefully. This course examines the types of data commonly available in
higher education, how it can be accessed, guidelines for preparing the data for analysis,
and best practices around storing, securing, and managing multiple data sets.
HED 606: Advanced Analytic Methods for Higher Education
Data-informed decision-making often requires analysis that is more in-depth, complex,
and sophisticated than can be done in a spreadsheet. Predictive analytics in particular
defy simple tools and approaches, yet show substantial promise in improving student
outcomes and operational efficiency with universities. This course will teach participants
the skills necessary to perform more advanced analytic procedures and provide a
conceptual understanding of how the procedures work. Using Rapidminer, students will
configure several differnt models and evaluate the output of those models in order to
choose the one that best informs decision-making.
HED 607: Visualization & Presentation for Higher Education
An analysis, regardless of how complex, is only as good as the analyst’s ability to explain
it to decision-makers. This course is focused on the process of creating visualizations
and tables that clearly communicate. We will discuss the principles of effective
visualization, the guidelines for creating a table or graph that are accurate and clear,
and the use of visualization in the analytic process. Using Tableau, students will create
a variety of different visualizations and integrate them into presentations ready for senior
leadership.
HED 608: Trends in Advanced Analytic Methods for Higher Education
General data mining techniques are useful, but certain applications have proven of
particular interest to higher education practitioners. This course will introduce those
topics, the principle literature around them including discussion of their efficacy in
improving higher education outcomes, and future technological advancements to watch.