Natural Language Processing
Washington University in St. Louis · MO · CSE5270
Natural Language Processing is a subject at Washington University in St. Louis, MO. It covers topics like computational-linguistics, deep-learning, machine-learning, natural-language-processing. It is part of 10 degrees. The information below is compiled from public course material — approximate, not official.
Washington University in St. Louis
CSE5270
3.00
Topics covered
Degrees that include Natural Language Processing
- Computer Science + Mathematics (CSE), BS
- Computer Science + Mathematics (CSE), Second Major
- Data Mining & Machine Learning Certificate (CSE)
- Mathematics and Computer Science Major
- Robotics and Intelligent Systems, MEng
- Statistics, Accelerated BA/MA, Applied Data Science Concentration
- Statistics, Accelerated BA/MA, Statistics Concentration
- Statistics and Data Science, MA, Applied Data Science Concentration
- Statistics and Data Science, MA, Statistics Concentration
- Statistics and Data Science, MA, Statistics for Political Science PhD Students Concentration
Frequently asked questions
What is Natural Language Processing about?
Natural Language Processing covers topics like computational-linguistics, deep-learning, machine-learning, natural-language-processing.
Which degrees include Natural Language Processing?
Natural Language Processing is part of 10 degrees, including Computer Science + Mathematics (CSE), BS, Computer Science + Mathematics (CSE), Second Major, Data Mining & Machine Learning Certificate (CSE), Mathematics and Computer Science Major, Robotics and Intelligent Systems, MEng.
How many credit points is Natural Language Processing?
Natural Language Processing at Washington University in St. Louis is typically around 3.00 credit points. Approximate — confirm with the university.
Where is Natural Language Processing taught?
Natural Language Processing is taught at Washington University in St. Louis, MO.
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Sources: Washington University in St. Louis public course catalogue. Information is compiled and summarised — not copied verbatim — and is approximate; always confirm with the original source.
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