%0 Conference Proceedings %T A Balanced and Broadly Targeted Computational Linguistics Curriculum %A Manning, Emma %A Schneider, Nathan %A Zeldes, Amir %Y Jurgens, David %Y Kolhatkar, Varada %Y Li, Lucy %Y Mieskes, Margot %Y Pedersen, Ted %S Proceedings of the Fifth Workshop on Teaching NLP %D 2021 %8 June %I Association for Computational Linguistics %C Online %F manning-etal-2021-balanced %X This paper describes the primarily-graduate computational linguistics and NLP curriculum at Georgetown University, a U.S. university that has seen significant growth in these areas in recent years. We reflect on the principles behind our curriculum choices, including recognizing the various academic backgrounds and goals of our students; teaching a variety of skills with an emphasis on working directly with data; encouraging collaboration and interdisciplinary work; and including languages beyond English. We reflect on challenges we have encountered, such as the difficulty of teaching programming skills alongside NLP fundamentals, and discuss areas for future growth. %R 10.18653/v1/2021.teachingnlp-1.11 %U https://aclanthology.org/2021.teachingnlp-1.11 %U https://doi.org/10.18653/v1/2021.teachingnlp-1.11 %P 65-69