The University of Connecticut’s MS in Business Analytics & Project Management degree provides you with the project management knowledge, tools, and techniques you need to effectively plan, organize, and deliver projects and programs. Learning in the program comprises a combination of lectures, class discussions, and presentations to peers. The curriculum is covered in 37 credit hours, including five 3-credit courses in Business Analytics, 1 credit in technical communications, four 3-credit courses in Project Management, and 9 credit hours in elective courses. Elective courses can be chosen from the wide array of offerings in the School’s professional MBA program, and may include experiential learning credits. Students are allowed to take on electives from other University of Connecticut graduate programs but only with the approval of the Program Director. Experiential learning opportunities offer students a chance to apply their advanced skills to challenging real world business problems. These opportunities include the Innovation Accelerator and the Experiential Learning Collaborative, Capstone project, along with various internships with partner corporations.
UConn’s Innovation Accelerator (IA) assists high-tech entrepreneurial ventures in addressing numerous challenges associated with the identification and capture of business opportunities. The IA utilizes interdisciplinary project teams comprised of graduate students that innovatively solve complex business issues for Connecticut’s technology-based entrepreneurial ventures. The Experiential Learning Collaborative (ELC) brings UConn students and the business community together through collaboration on real-world projects. Participation in collaborative projects introduces students to advanced business practices and helps business executives identify potential employees among UConn students. The Capstone project involves a live data analytics project, where students integrate their knowledge of data analytics including predictive modeling, data management, process models, and data mining techniques to investigate a real problem. They then use their project management skills to complete the project within scope, time and budget constraints.