Training Sessions Unveiled for Analytics Summit 2019 Presented by the UC Center for Business Analytics
Training session curriculums and schedules have been announced for Analytics Summit 2019 presented by the University of Cincinnati Center for Business Analytics.
Training session curriculums and schedules have been announced for
Analytics Summit 2019 presented by the University of Cincinnati Center
for Business Analytics. The 8th annual event is being held
April 1-3, 2019 at the Sharonville Convention Center in Cincinnati, Ohio.
All training sessions will be held April 1 and 2 from 8:30 a.m. until 5
p.m. (EST), with the exception of the Analytics for Executives session
being held April 2nd from noon until 5 p.m. Hands-on,
practical training techniques will give students the opportunity to
interact directly with expert instructors and peers, and get immediate
feedback along with answers to technical and business-related questions.
Sessions summaries follow. Prospective students are encouraged to visit
the event
website for a complete session outline, prerequisites, and details.
Advanced
MS Power BI - This course takes a deep dive into advanced level
Power BI skills, covering lesser-known but more advanced skills from the
Power BI set of features. The session will be led by Geoff Marsh, BI
Practice Leader from Amend Consulting, and Derek Sasthav, Project Leader
at Amend.
Machine
Learning with R - Learn the fundamentals and application of modern
machine learning tasks. This course will cover unsupervised techniques
to discover the hidden structure of datasets along with supervised
techniques for predicting categorical and numeric responses via
classification and regression. Session instructors will be Brad Boehmke,
Director of Data Science at 84.51o, and Brandon Greenwell,
Senior Data Scientist at Ascend Innovations.
Advanced
Tableau Training - This two-day workshop on Tableau will cover
intermediate and advanced topics. Attendees should have attended
previous "Introduction to Tableau" training or have significant
experience using Tableau in a professional environment. Course content
will include advanced chart types and business dashboards, advanced
calculations in Tableau, using calculations, parameters, and table
calculations, and other topics. Jeff Shaffer, Tableau Zen Master, will
lead this session.
Big
Data with Hadoop & Spark - Attendees will learn how these
powerful tools function and form the core of big data analytics systems.
The emphasis of this course will be on understanding the fundamental
principles of big data systems using Hadoop and Spark and will extend
beyond basics to introduce some technical components. Andrew Harrison,
Assistant Professor of Information Systems at the Lindner School of
Business at UC, and Zhe (Jay) Shan, Assistant Professor in Dept.
Information Systems and Analytics at Miami University Farmer School of
Business will lead this session.
Analytics
for Executives - This half-day session led by Glenn Wegryn,
Executive Director at the UC Center for Business Analytics is intended
for business leaders at the Director level and above. It will focus on
providing a fundamental understanding of what analytics is, examples of
successful applications in financial and other industries, how to get
started, and what resources, skill sets, organization, and cultural
elements need to be in place for long-term success.
Complete details and registration information can be found on the Analytics
Summit 2019 event registration site.
About
the University of Cincinnati’s Center for Business Analytics
The Center for Business Analytics at the University of Cincinnati’s Carl
H. Lindner College of Business is a corporate-academic partnership
that brings together a multidisciplinary group of businesses,
organizations, faculty, and students to provide education and an
exchange of ideas and best practices regarding the application of
data-driven analytical methods for enhancing organizational performance.
In collaboration with its corporate sponsors, the center provides
symposia, student projects, community training, and applied research
focused on the use of techniques such as data visualization, data
mining, predictive modeling, simulation, and optimization to solve
important problems faced by businesses, government and non-profit
organizations.
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