Professional Short Courses
K-State Olathe connects the classroom to the workplace by offering leading edge classes in the latest technologies, innovations, techniques and research to help you advance your career.
Learning is different when you're already in the workforce. Traditional methods may be less applicable to your work-life realities and pressing “pause” in your life and career is not a possibility.
K-State Olathe hosts professional short courses designed to advance your career and enable you to solve critical business issues or leverage complex data for a competitive edge.
Learn to Apply Big Data to Your Business
An Application & Methodology Short Course
Join us for a 3-day workshop where you’ll expand your understanding of computational infrastructure and software tools that support big data applications development.
Participants will gain highly applied, hands-on experience using open-source and commercial solutions, including:
- Apache Hadoop
- Amazon Elastic Compute Cloud
- MapReduce programming model
- IBM Blue Mix platform as a service
When: Aug 12th 1-4pm, Aug 14th 1-5pm, Aug 19th 1-4pm
Where: K-State Olathe, 22201 W. Innovation Dr., Olathe, KS 66061-1304
By GPS: K-State Olathe, 22201 College Blvd., Olathe, KS 66061
Cost: $500 for 3-day program
Who should attend: Managers and Directors in Data Science, Analytics and CRM, plus Applications Developers in Business Intelligence and Business Analytics
What to bring: Laptop
Instructor: Bill Hsu
Dr. William H. Hsu is an associate professor of Computing and Information Sciences at Kansas State University. He received a B.S. in Mathematical Sciences and Computer Science and an M.S.Eng. in Computer Science from Johns Hopkins University in 1993, and a Ph.D. in Computer Science from the University of Illinois at Urbana-Champaign in 1998. His dissertation explored the optimization of inductive bias in supervised machine learning for predictive analytics. At the National Center for Supercomputing Applications (NCSA) he was a co-recipient of an Industrial Grand Challenge Award for visual analytics of text corpora. His research interests include machine learning, probabilistic reasoning, and information visualization, with applications to cybersecurity, education, digital humanities, geoinformatics, and biomedical informatics. Current work in his lab deals with: spatiotemporal mapping of opinions, crimes, and other events; data mining and visualization in education research; graphical models of probability and utility for information security; analysis of heterogeneous information networks; and domain-adaptive models of large natural language corpora and social media for text mining, link mining, sentiment analysis, and recommender systems. Dr. Hsu is editor of the forthcoming book Emerging Methods in Predictive Analytics, and has over 50 refereed publications in conferences, journals, and books, plus over 35 additional publications.