AI314
NATURAL LANGUAGE PROCESSING
- Course Code
- AI314
- Semester
- Sixth Term (Spring)
- Theory+Practice
- 3 + 1
- ECTS
- 5
| Course Type | Compulsory Course |
|---|---|
| Course Level | Bachelor's Degree |
| Year of Study | 3 |
| Semester | Sixth Term (Spring) |
| ECTS | 5 |
| Name of Lecturer(s) | - |
| Learning Outcomes |
At the end of this course, the students; |
| Mode of Delivery | |
| Prerequisites | Yes(AI313) |
| Recommended Optional Programme Components | |
| Course Description | This course introduces the computational techniques used to process and analyze human language. Topics include tokenization, part-of-speech tagging, parsing, sentiment analysis, named entity recognition, word embeddings, and modern transformer-based models such as BERT and GPT. Practical projects using Python and libraries like NLTK, spaCy, and HuggingFace will be emphasized. |
| Course Contents | |
| Recommended or Required Reading | * Jacob Eisenstein, "Introduction to Natural Language Processing", MIT Press, 2019. * Jurafsky, D., & Martin, J. H., "Speech and Language Processing", 3rd ed. draft, 2023. * HuggingFace documentation and tutorials. |
| Planned Learning Activities and Teaching Methods | |
| Assessment Methods and Criteria | |
| Language of Instruction | - |
| Work Placement(s) | No |