Tuesday, December 6, 2011

Stanford University: Natural Language Processing course

The following online course on Natural Language Processing from Stanford University (sorry for advertising a non-DIT course!) may be useful for some dissertations:

There is a range of other courses listed at the bottom that sound really interesting if you have time such as Probabilistic Graphic Models, Machine Learning and Information Theory.
Course Description
The course covers a broad range of topics in natural language processing, including word and sentence tokenization, text classification and sentiment analysis, spelling correction, information extraction, parsing, meaning extraction, and question answering, We will also introduce the underlying theory from probability, statistics, and machine learning that are crucial for the field, and cover fundamental algorithms like n-gram language modeling, naive bayes and maxent classifiers, sequence models like Hidden Markov Models, probabilistic dependency and constituent parsing, and vector-space models of meaning.


  1. Again apologies for advertising a non-DIT course! The people who are running this course, Jurafsky and Marint, are really god and wrote what is pretty much the definitive textbook on natural language processing. Defintley worth a look.

  2. Courses postponed: