Due to current COVID-19 pandemic, the whole or a part of the class may be taught online. Please follow this page for further updates/information.
This course is a practical, broad and fast-paced introduction to Natural Language Processing (NLP). The course covers a variety of machine learning techniques and their applications in NLP and computational linguistics. The schedule includes for more information on the topics and course material.
This is a 9ECTS course compulsory for the BA studies in the International Studies in Computational Linguistics (ISCL). Master’s students can take the course as a “Hauptseminar” with additional work (a term project/paper). The course is also open to students of other degree programs with appropriate background. Please contact the instructor before signing up if you are unsure whether you meet the requirements or not. See the course syllabus for further details.
To register for the course, and access to some of the course material, you need to complete an introductory assignment. Please complete this exercise before Monday 22th of April.
- Daniel Jurafsky and James H. Martin (2009) Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition. Pearson Prentice Hall, second edition (JM) chapters from 3rd edition draft (JM3)
- Trevor Hastie, Robert Tibshirani, and Jerome Friedman (2009), The Elements of Statistical Learning: Data Mining, Inference, and Prediction. Springer-Verlag, second edition. (HTF) available online
Due to current COVID-19 pandemic, the whole or a part of the class may be taught online. The places indicated below are only relevant after the normal teaching activities are resumed
|Lectures||Monday 12:00 / Wednesday 14:00, room 0.02|
|Lab||Friday 12:00, room 0.02|
|First Lecture||Wednesday April 22|
|Lecturer||Çağrı Çöltekin <firstname.lastname@example.org>|
|Tutor||Maximilian Gutsche <email@example.com>|
|Office hours||Monday 14:00-15:00|