Studying Computational Linguistics at Pitt: A Guide(Last modified 11/20/2020)
OverviewWith Artificial Intelligence (AI) finally maturing and natural language becoming its central interface, this is a good time to be a computational linguist. If you want to major in linguistics with a special focus on computational linguistics, or are just plain curious about computational methods, Pitt is a great place to be. This document gives you an overview of the classes and resources available at Pitt and beyond.
TimelineComputational methods are all about habit-building, which means you don’t become a computational linguist in one short semester. Get an early start: freshman is a good time to pick up a programming language, and, if you haven’t heard, that language should be Python. You should continue learning and training through the sophomore and junior years, taking more courses (I recommend at least one computational course a semester) and gaining exposure through collaborating with faculty members and participating in computational linguistics research projects. In your senior year, you should look beyond academia and look for career opportunities or plan to seek further training through grad school.
But what if you only have so much room in your schedule? It's never too late to pick up some computational training before you graduate, which will make you a stronger linguist. Taking a couple of key courses will give you this foundation. Many students have done this and found it instrumental in their post-graduation career building.
CoursesIf you never took a programming course before, you should do so first by taking CS 8 or CS 12. Both teach Python, and CS 12 in particular is tailored for students with a humanities background. Many students don't find themselves immediately taking to programming, but don't be discouraged! When you get to LING 1330 "Intro to Computational Linguistics", you will see how the training you picked up lines up neatly with your linguistic interests.
Additional CoursesIf you are picking up a major or minor in computer science, you should consider taking some of the following courses. They are offered through Pitt's CS department and also CMU's Language Technologies Institute (LTI), and often come with CS prerequisites such as Java, algorithms and databases.
Research and Industry ExperienceAnother critical component of computational linguistics is application: a practical experience of having actually applied your computational knowledge and training to a research project or a real-world problem. A research experience you can gain through LING 1903 Directed Research as well as collaborating with linguistics faculty, CS faculty and people at the LTI. You can gain job experience through LING 1900 Linguistic Consulting and Internship, which places students at local companies in Pittsburgh, many of which are technology firms. Such opportunities abound, which has been one of the unique advantages our students have been enjoying.
Knowledge and SkillsAt the core, you will need a solid training in computational linguistics and its methods:
Get InvolvedYou should join PyLing (Pitt Python Linguistics Group), which has become a thriving community of computational linguists at Pitt and CMU. You can continue your learning through guest presentations and tutorials, and get to know NLP researchers, practitioners and alumni working in the field. You should also check out the LTI colloquium and the CS Intelligent Systems colloquium, which often feature well-known NLP researchers from around the world.
Questions?There is so much more information than I could possibly put all in here! If you have are curious and/or have questions, come talk to me.