Cornell University
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Digital Technology Immersion

In Spring 2016, Cornell’s Samuel Curtis Johnson Graduate School of Business and the Department of Information Science in Computing and Information Science (CIS) launched the Digital Technology Immersion program, pairing students from both schools to work collaboratively on projects for partnering companies like Verizon, Ensighten and Thomson Reuters.

The result is mutually beneficial: MBA students bolster skill sets in areas like data analytics, ubiquitous computing, and Web design and programming, while Information Science Master of Professional Studies (MPS) students are schooled in areas like leadership, project management, and entrepreneurship for scientists and engineers.

In this immersion, MPS students are signed up for a project course (3 credits) in which they will be working on a project sponsored by an industry client. In the inaugural Spring 2016 semester, client companies included Verizon, Genentech, GiveNext, and Workday, among others. The course will have weekly meetings to discuss business and management aspects of technology and information science through a series of guest lecturers from the industry, and reserve time to work on projects. Students will also have an opportunity to work with experts on corporate practices to enhance professional skills in areas such as public speaking, team conflict resolution, and more.

Taking this course fulfills your MPS project requirement. 

In addition, students will sign up for 6 credits of Johnson courses, chosen from the following list (final list is TBD):

• NBA 5070    Entrepreneurship for scientists and engineers    3 credits

• NBA 5150    Leadership theory and practice    3 credits

• NBA 5410    Project management    1.5 credits

• NBA 6010    Electronic commerce    3 credits

• NBA 6170    Emerging technology markets    1.5 credits

• NBA 6180    Global innovation and technology commercialization 1.5 credits

• NBA 6650    Strategic management of technology and innovation    3 credits

• NBA 6920    Advanced topics in data analytics    3 credits