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Blended Learning

The NYU Stern MS in Business Analytics is based on a blended learning approach combining both synchronous (in-person classroom time) and asynchronous learning (independent study).

Modules are divided into three phases: pre-module, module, and post-module.

Blended Learning

Pre-module: Research Phase
This begins 4-6 weeks prior to the in-class teaching session. Students prepare for the module by completing qualitative and quantitative assignments that include; readings and cases, tutorials and diagnostics, and exercises and written assessments. Completion of the pre-module material ensures a more rigorous and productive classroom experience.

Module: Residential Period
Students and leading faculty, industry experts, and practitioners come together for valuable “in-class” residential periods. The classroom provides a dynamic environment for discovery and collaboration with your classmates.

Post-module: Application
The post-module is designed as the implementation phase of the module. Students are challenged to apply the material and concepts covered during the pre-module phase and residential period to solidify their learning. Deliverables are in the form of case studies, written assignments, projects, and group work.

Throughout the pre- and post-module phase, students will be part of study groups that encourage collaboration and peer-to-peer learning.