  NLP's sphere of influence went much beyond computer science research and the
development of software applications in the past decade. We see people using
NLP methods in a range of academic disciplines from Asian Studies to Clinical
Oncology. We also notice the presence of NLP as a module in most of the data
science curricula within and outside of regular university setups. These
courses are taken by students from very diverse backgrounds. This paper takes a
closer look at some issues related to teaching NLP to these diverse audiences
based on my classroom experiences, and identifies some challenges the
instructors face, particularly when there is no ecosystem of related courses
for the students. In this process, it also identifies a few challenge areas for
both NLP researchers and tool developers.
