IN5550 – Neural Methods in Natural Language Processing
Course Overview
IN5550 studies advanced techniques in Natural Language Processing (NLP), focusing on deep learning and neural networks. The course covers topics such as representation learning, document classification, sequence tagging, and natural language generation. It emphasizes practical components and current research problems in NLP.
Learning Outcomes
- Familiarity with techniques for learning dense representations of natural language
- Understanding of various types of neural networks and their NLP applications
- Ability to apply NLP tools for data preparation in representation learning
- Knowledge of transfer and multi-task learning in NLP
- Skills to design and execute large-scale experiments with neural network toolkits
- Ability to assess benefits and challenges of neural learning in NLP
- Critical reading of relevant NLP research literature
- Skills to train and fine-tune large language models
Grading Scale
IN5550 uses a pass/fail grading scale.
Important Information
Teaching Format
Four hours per week: two hours lectures, two hours hands-on laboratory work
Examination
Practical project and summary report, both must be passed in the same semester
Mandatory Assignments
Must be approved to qualify for the final exam
Admission
Open to UiO students and Nordic citizens as single course students
Recommended Previous Knowledge
IN4080 – Natural Language Processing
Overlapping Courses
IN9550, INF5820, INF9820
Course Language
English
Resit Exam
Postponed exams not offered, but deferred submission may be possible
Overlapping Courses with IN5550 – Neural Methods in Natural Language Processing
Note: This visualization shows the number of credits that overlap between IN5550 and other courses. Hover over the bars for more information about each course.
Weekly Schedule for IN5550
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2 hoursLectures
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2 hoursLaboratory Work