Natural Language Processing
Software Engineering
Faculty of Engineering
First Cycle (Bachelor's Degree)
| Course Unit Title | Course Unit Code | Type of Course Unit | Level of Course Unit | Year of Study | Semester | ECTS Credits |
|---|---|---|---|---|---|---|
| Natural Language Processing | YZM419 | Elective | Bachelor's degree | 4 | Fall | 5 |
Name of Lecturer(s)
Assistant Prof. Dr. Kaplan KAPLAN
Learning Outcomes of the Course Unit
1) Know rule-based and statistical methods and Natural Language analysis techniques
2) Understands the uncertainty problem in Natural Language Processing and knows the removal techniques.
3) Know syntactic and semantic Natural Language Processing methods
4) Knows the importance and properties of compilation in Natural Language Processing.
5) Understands language models.
6) Understands Zipf's laws and N-grams
7) Knows the word type labeling methods and their application areas
8) Knows word stemming and rooting methods
9) Knows the methods of determining phrases
10) Knows machine translation methods
Program Competencies-Learning Outcomes Relation
| Program Competencies | |||||||||||||
| 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | ||
| Learning Outcomes | |||||||||||||
| 1 | Middle | No relation | Low | Low | No relation | No relation | No relation | Low | Middle | No relation | High | No relation | |
| 2 | Middle | No relation | Low | Middle | No relation | No relation | No relation | Low | Middle | No relation | High | No relation | |
| 3 | Middle | No relation | Low | Middle | No relation | No relation | No relation | Low | Low | No relation | High | No relation | |
| 4 | Middle | No relation | Low | Low | No relation | No relation | No relation | Low | Middle | No relation | Middle | No relation | |
| 5 | Middle | No relation | Low | Low | No relation | No relation | No relation | Low | Middle | No relation | High | No relation | |
| 6 | Middle | No relation | Low | Low | No relation | No relation | No relation | Low | Middle | No relation | High | No relation | |
| 7 | Middle | No relation | Low | No relation | No relation | No relation | No relation | Low | Low | No relation | Middle | No relation | |
| 8 | Middle | No relation | Low | Low | No relation | No relation | No relation | Low | Middle | No relation | High | No relation | |
| 9 | Middle | No relation | Low | No relation | No relation | No relation | No relation | Low | Low | No relation | Middle | No relation | |
| 10 | Middle | Low | Middle | No relation | No relation | No relation | No relation | Low | Low | No relation | High | No relation | |
Mode of Delivery
Face to Face
Prerequisites and Co-Requisites
None
Recommended Optional Programme Components
Not Required
Course Contents
Inputs, Speech and Speech Recognition, Words and Convrter, N-grams, Word Labeling, Statistical Language Models, Grammars, Statistical Parsing, Semantics, Information Extraction, Query Answering, Text Summarization
Recommended or Required Reading
Planned Learning Activities and Teaching Methods
1) Lecture
2) Lecture
3) Lecture
4) Question-Answer
5) Question-Answer
6) Question-Answer
7) Discussion
8) Discussion
9) Discussion
Assessment Methods and Criteria
Contribution of Midterm Examination to Course Grade |
40% |
|---|---|
Contribution of Final Examination to Course Grade |
60% |
Total |
100% |
Language of Instruction
Turkish
Work Placement(s)
Not Required