What do we teach in NLP courses?¶
Day 1: June 10th from 12:00 to 13:00 UTC-04:00 or ET
How to connect: Zoom via Underline
We would like to address some of your questions during the panel discussion. Please write your questions on this topic in this Google document.
NLP is a rapidly growing field which brings unique challenges to the educators. Many of us grapple with at least some of the following questions.
How much time should we spend on classical NLP vs. deep learning NLP in an introductory NLP course?
What’s the role of linguistics in NLP courses today?
What should be the prerequisites for introductory NLP courses? Should we presuppose supervised and unsupervised machine learning , deep learning, and some basic linguistics knowledge?
Most of the NLP courses teach different NLP models, NLP pipeline tasks, applications, evaluation, and tools. What is the most constructive way to weave these things together?
NLP is changing fast and the skills we teach today risk being outdated to the students in a matter of years. How do we prepare student for this constant change in the field?
How do we effectively teach ethical and responsible use of NLP models?
What topics should we save for advanced NLP course?
In this panel discussion we’ll hear thoughts of our amazing panelists on some of the above questions.
Panelists¶
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Isabelle Augenstein is an associate professor in Computer Science at the University of Copenhagen. Her main research interests are fact checking, low-resource learning and explainability. She has developed and taught NLP courses at University of Copenhagen and University College London. She has also given tutorial and talks at a number of summer schools. |
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Emily M. Bender is a Professor of Linguistics and an Adjunct Professor in Computer Science and Engineering at the University of Washington. She is the Director of the Computational Linguistics Master’s program. She has a wealth of teaching and mentoring experience, and has taught many courses and seminars in Linguistics, Computational Linguistics, and Ethics in NLP in the past two decades. (Check out her NLP pedagogy interview). |
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Yoav Goldberg is a Senior Lecturer in Computer Science at Bar Ilan University. He has taught a number of courses and seminars in NLP. His famous tutorial on deep learning NLP, A Primer on Neural Network Models for Natural Language Processing, and his book Neural Network Methods for Natural Language Processing Synthesis Lectures on Human Language Technologies are widely used in deep learning NLP courses all over the world. |
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Dan Jurafsky is Professor of Linguistics and Professor of Computer Science at Stanford University. He has designed and taught a number introductory and advanced courses in Linguistics, Psycholinguistics, and NLP in the past two decades. Also, he is the co-author of one of the best books in NLP, Speech and Language Processing. This book and his co-authored short NLP videos have inspired many people in the world. (Check out his NLP pedagogy interview). |
