| TDDE09 |
Natural Language Processing, 6 ECTS credits.
/Språkteknologi/
For:
CS
D
DAV
IT
U
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OBS! |
The course is not available for exchange students
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Prel. scheduled
hours: 48
Rec. self-study hours: 112
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Area of Education: Technology
Main field of studies:
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Advancement level
(G1, G2, A): A
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Aim:
Natural Language Processing (NLP) develops techniques for the analysis and interpretation of natural language, a key component of smart search engines, personal digital assistants, and many other innovative applications. The goal of this course is to provide students with a theoretical understanding of and practical experience with the advanced algorithms that power modern NLP. The course focuses on methods that involve machine learning on text data. On completion of the course, the student should be able to:
- explain state-of-the-art NLP algorithms and analyse them theoretically
- implement NLP algorithms and apply them to practical problems
- design and carry out evaluations of NLP components and systems
- seek, assess and use scientific information within the area of NLP
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Prerequisites: (valid for students admitted to programmes within which the course is offered)
Discrete mathematics. Good knowledge of programming, data structures, and algorithms. Basic knowledge of probability theory and optimisation. Previous courses in machine learning are recommended but no requirement for the course.
Note: Admission requirements for non-programme students usually also include admission requirements for the programme and threshhold requirements for progression within the programme, or corresponding.
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Supplementary courses:
Text Mining
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Organisation:
The course is given in the form of lectures, lab sessions, and seminars in connection with a minor project.
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Course contents:
State-of-the-art NLP algorithms for the analysis and interpretation of words, sentences, and texts. Relevant machine learning methods based on statistical modelling, combinatorial optimisation, and neural networks. NLP applications. Validation methods. NLP tools, software libraries, and data. NLP research and development.
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Course literature:
Lecture notes provided by the department
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Examination: |
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Written examination
Practical assignments
Project assignments
Optional written tests
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2 ECTS
2 ECTS
2 ECTS
0 ECTS
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The optional written tests give bonus points for the first attempt at the written examination. The final grade for the course is the median of the grades awarded for LAB1, TEN1, and UPG1. |
Course language is English.
Department offering the course: IDA.
Director of Studies: Jalal Maleki
Examiner: Marco Kuhlmann
Course Syllabus in Swedish
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