Course Information
SemesterCourse Unit CodeCourse Unit TitleT+P+LCreditNumber of ECTS CreditsLast Updated Date
8BLMS404Natural Language Processing3+0+03503.10.2024

 
Course Details
Language of Instruction Turkish
Level of Course Unit Bachelor's Degree
Department / Program Computer Engineering
Type of Program Formal Education
Type of Course Unit Elective
Course Delivery Method Face To Face
Objectives of the Course Introduce Natural Language and its applications; Show its possible applications/realizations and associated constraints.
Course Content Morphological analysis of the language;Different grammar structure; Clustering and Classification Algorithms;Information Retrieval; Question Answering, Collacation.
Course Methods and Techniques
Prerequisites and co-requisities None
Course Coordinator Asist Prof.
Name of Lecturers Asist Prof.Dr. BAŞAK BULUZ KÖMEÇOĞLU
Assistants None
Work Placement(s) No

Recommended or Required Reading
Resources Natural Language Understanding, J.Allen, Benjamin-Cummings.
Course Notes Lectures, Question-Answer, Project.
Assignments Bir grup projesi
Exams Vize ve Final Sınavları

Course Category
Mathematics and Basic Sciences %0
Engineering %10
Engineering Design %10
Social Sciences %0
Education %0
Science %0
Health %0
Field %80

Planned Learning Activities and Teaching Methods
Activities are given in detail in the section of "Assessment Methods and Criteria" and "Workload Calculation"

Assessment Methods and Criteria
In-Term Studies Quantity Percentage
Mid-terms 1 % 20
Project 1 % 20
Final examination 1 % 60
Total
3
% 100

 
ECTS Allocated Based on Student Workload
Activities Quantity Duration Total Work Load
Course Duration 14 3 42
Hours for off-the-c.r.stud 14 3 42
Mid-terms 1 2 2
Practice 14 2 28
Project 1 10 10
Final examination 1 2 2
Total Work Load   Number of ECTS Credits 4 126

 
Course Learning Outcomes: Upon the successful completion of this course, students will be able to:
NoLearning Outcomes
1 The student will know the convenience of using Natural Language in our ordinary life.
2 The student will learn the algorithms and methods on the Natural Language Processing domain.
3 The students will recognize and use the domestic and foreign tools.
4 The student will learn all the concept about Natural Language Processing.

 
Weekly Detailed Course Contents
WeekTopicsStudy MaterialsMaterials
1 Introduction to Natural Language Processing.
2 Linguistic Essentials.
3 Language Models.
4 Grammer and Languages.
5 Syntactic Analysis.
6 Morphological Anaysis.
7 Review.
8 Midterm exam.
9 Cloud Development: Dev 2.0 platforms. Software Architecture.
10 Text Categarization.
11 Information Retrieval.
12 Text Indexing and Retrieval.
13 Question Answering.
14 Review.

 
Contribution of Learning Outcomes to Programme Outcomes
P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11
All 1
C1
C2
C3
C4

  bbb

  
  https://obs.gedik.edu.tr/oibs/bologna/progCourseDetails.aspx?curCourse=243253&curProgID=5607&lang=en