Information Package / Course Catalogue
Large Language Models
Course Code: MCS524
Course Type: Area Elective
Couse Group: Second Cycle (Master's Degree)
Education Language: English
Work Placement: N/A
Theory: 3
Prt.: 0
Credit: 3
Lab: 0
ECTS: 6
Objectives of the Course

Introducing the fundamentals of statistical natural language processing ,neural approaches, concepts, and applications. Learning current transformer architectures. Enabling students to statistical natural language processing projects with Python.

Course Content

The current technical approaches for linguistic problems, parsing, sentence meaning, word senses, semantic role labeling, coreference resolution, machine translation, chatbots.

Name of Lecturer(s)
Learning Outcomes
1.Understanding how core natural language processing tasks can be applied with statistical and neural approaches.
2.Understanding how core natural language processing tasks can be applied with statistical and neural approaches.
3.Understanding how core natural language processing tasks can be applied with statistical and neural approaches.
4.Developing natural language processing projects for various tasks
5.Developing natural language processing projects for various tasks
Recommended or Required Reading
1.Dan Jurafsky and James H. Martin, “Speech and Language Processing”, 3rd Ed., Prentice Hall, 2023.
Weekly Detailed Course Contents
Week 1 - Theoretical & Practice
Introduction
Week 2 - Theoretical & Practice
Core Concepts
Week 3 - Theoretical & Practice
Context-Free Grammars and Constituency Parsing
Week 4 - Theoretical & Practice
Dependency Parsing
Week 5 - Theoretical & Practice
Relation and Event Extraction
Week 6 - Theoretical & Practice
Word Senses and Wordnet
Week 7 - Theoretical & Practice
Lexicons for Sentiment, Affect and Connotation
Week 8 - Theoretical & Practice
Coreference Resolution
Week 9 - Theoretical & Practice
Transformers and Pretrained Language Models
Week 10 - Theoretical & Practice
Fine-tuning and Masked Language Models
Week 11 - Theoretical & Practice
Machine Translation
Week 12 - Theoretical & Practice
Question Answering Systems and Information Retrieval
Week 13 - Theoretical & Practice
Chatbots and Dialogue Systems
Week 14 - Theoretical & Practice
Chatbots and Dialogue Systems
Assessment Methods and Criteria
Type of AssessmentCountPercent
Attending Lectures1%5
Presentation1%5
Midterm Examination1%20
Final Examination1%70
Workload Calculation
ActivitiesCountPreparationTimeTotal Work Load (hours)
Lecture - Theory143384
Presentation 1516
Individual Work140114
Midterm Examination120222
Final Examination120323
TOTAL WORKLOAD (hours)149
Contribution of Learning Outcomes to Programme Outcomes
PÇ-1
PÇ-2
PÇ-3
PÇ-4
PÇ-5
PÇ-6
PÇ-7
PÇ-8
PÇ-9
OÇ-1
3
3
3
3
4
3
4
3
3
OÇ-2
4
4
4
3
5
4
3
4
3
OÇ-3
3
3
5
5
5
4
3
5
5
OÇ-4
5
4
5
4
4
4
5
5
4
OÇ-5
3
3
3
3
4
3
4
3
3
Adnan Menderes University - Information Package / Course Catalogue
2026