In this paper we provide an account of how we ported a text and data mining course online in summer 2020 as a result of the COVID-19 pandemic and how we improved it in a second pilot run. We describe the course, how we adapted it over the two pilot r
uns and what teaching techniques we used to improve students' learning and community building online. We also provide information on the relentless feedback collected during the course which helped us to adapt our teaching from one session to the next and one pilot to the next. We discuss the lessons learned and promote the use of innovative teaching techniques applied to the digital such as digital badges and pair programming in break-out rooms for teaching Natural Language Processing courses to beginners and students with different backgrounds.
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.
