The NLP MS program is intended for students who already have a considerable background in computer science.

The minimum background for consideration for admission to the program is the following:

• A B.A. in Computer Science
• A class in Discrete Math (the equivalent of UCSC's CSE 16: Applied Discrete Mathematics)
• An upper division class in Data Structures and Algorithms (the equivalent of UCSC's CSE 101: Introduction to Data Structures and Algorithms)
• At least one class in Probability and Statistics (the equivalent of UCSC's CSE 107: Probability and Statistics for Engineers or STAT 131: Introduction to Probability Theory)
• An overall GPA of 3.0 or better (on the 4.0 GPA scale) or the equivalent
• Excellent programming skills

The preferred background for consideration for admission to the program is:

• A B.S. in Computer Science
• An overall GPA of 3.2 or better (on the 4.0 GPA scale) or the equivalent
• A class in NLP or Linguistics (the equivalent of UCSC's CSE 143: Introduction to Natural Language Processing)
• A class in Probability and Statistics with a grade of B+ or better (the equivalent of UCSC's CSE 107: Probability and Statistics for Engineers or STAT 131: Introduction to Probability Theory)
• A class in Machine Learning (the equivalent of UCSC's CSE 142: Machine Learning)
• A class in Formal Languages and Automata Theory (the equivalent of UCSC's CSE 103: Computational Models)

Students who satisfy the minimum but not the preferred requirements might be conditionally admitted to the program and asked to take appropriate remedial courses before joining the program. None of these remedial courses can be counted as electives for the program.