CINCINNATI--(BUSINESS WIRE)--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.
