Introduction of data analytics in the engineering probability course: Implementation and lessons learnt

Abstract

Abstract Data analytics‐based tools are used extensively in industry, business, science, engineering, and medicine. Efforts are being made to transform the undergraduate course in engineering probability by incorporating the data analytics while retaining the concept‐driven topics. The author has been engaged in these efforts since 2017–2018. This manuscript reports on a number of data analytics‐based assignments alongside the traditional ones consisting of exercises requiring proofs, derivations, and calculations created during the fall quarter of 2018–2019. These assignments rely on computational tools and are connected to the theoretical concepts allowing the students to understand and appreciate the use of conceptual topics to practical application in machine vision, robotics, medical diagnostics, and so forth. The details on these assignments along with their implementation, results, and lessons learnt and conclusions drawn are presented.