This presentation covers how PI is used in real world projects in the Photonics curriculum at McMaster University. In these projects PI is used as an IoT data acquisition platform to demonstrate, apply and test error propagation, distribution and test of distribution, correlation and cross-validation, data rejection and signal processing. The Photonics program changed delivery of statistical analysis instruction from lecture format to the ‘experiential learning module’ using PI to cover data acquisition and statistical analysis. Projects include physical experimental setup to continuously measure environmental parameters (temperature, humidity, light, imaging, etc.) with a set of multi-modality sensors in an Internet-of-things (IoT) big data platform. As a platform, PI also supplies the visualization tools to deliver a multi-dimension view of complex data streams (e.g. time-lapse of statistical distribution) that accelerates students’ mastery of quantitative attribute measurements and improves the qualitative feedback from their projects.