The Business Analytics Using Forecasting free online course (MOOC) that I designed is opening in a week! As of today, 3000+ learners have joined from around the world and all ages. The welcome discussion board reveals an amazing crowd of grad students, professionals in a variety of fields, and even instructors.
I am glad to announce that the new editions of Practical Time Series Forecasting with R (Shmueli & Lichtendahl, Second Edition) and Practical Time Series Forecasting (Shmueli, Third Edition) are now available in print and ebook formats. The books are printed in the United States, Europe and India and are vailable globally. Kindle editions are also available worldwide.
I'll be offering a six-week free massive open online course (MOOC) on Business Analytics Using Forecasting starting October 17. This will be NTHU's first English-language MOOC hosted on the slick FutureLearn platform.
Our Institute of Service Science in collaboration with Taiwan's restaurant reservation website EZTABLE, is launching a data mining contest using two years of EZTABLE bookings data. The goal is to predict repeat-booking customers. This Taiwan-based open data mining contest is the first of its kind!
This Fall, I'm teaching two new elective courses at NTHU's Institute of Service Science: Business Analytics using Data Mining and Business Analytics using Forecasting. The two new courses join three existing elective courses to form the new concentration in Business Analytics. The most important part is our focus on humane and socially responsible analytics.
I describe collaborations with India start ups to create data mining contests on platforms such as kaggle.com. A great way to open real, interesting, local data. Provides business analytics students with real problems and data as well as access to the domain experts; gives start ups novel creative ideas for using their data, visibility to the world, and relationship with academia.
Last term I instructed over 200 students in two courses: "Business Analytics Using Data Mining" and "Forecasting Analytics". In each of the courses, students worked in teams on a project using real data, formulating a business problem and addressing it with data mining and/or forecasting tools. I have posted the top projects in the Students Projects area of my website (look for the 2013 projects). For each project, I posted the team's presentation slides and report.
I'll be describing and discussing my efforts and experience in re-designing the Business Analytics Using Data Mining course as a hybrid semi-MOOC course in tomorrow's 11am Analytics/INFORMS-Ed session at INFORMS. See here for location and details.