3. 강의목표
- Course Overview: This course covers the theoretical foundations of language models and discusses the characteristics and development trends of large language models. Additionally, through paper presentations and team projects, students actively share information and gain hands-on experience with the operational principles of large language models.
- Educational Objectives: The course provides opportunities to explore the latest natural language processing technologies and encourages students to think critically about how these technologies can be further developed.
5. 성적평가
(*Tentative) Paper presentation(50%), Project(50%)
6. 강의교재
| 도서명 |
저자명 |
출판사 |
출판년도 |
ISBN |
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- Lecture slides and recently published papers.
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0000
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8. 강의진도계획
(*Tentative Schedule)
1주차: Introduction
2주차: Language Model
3주차: Adaptation
4주차: Safety / TA Code Tutorial
5주차: Retrieval-Augmented Generation (RAG) / Multimodal LLM
6주차: Embodied AI
7주차: Project Proposal Presentation
8주차: Midterm Exam
9주차~14주차: Student discussion
15주차: Project Final Presentation
16주차: Final Exam
9. 수업운영
- Lecture Type: Offline
- Teaching Methods: Theoretical lectures, coding practice, paper presentation, student discussion, team projects.
11. 장애학생에 대한 학습지원 사항
- 수강 관련: 문자 통역(청각), 교과목 보조(발달), 노트필기(전 유형) 등
- 시험 관련: 시험시간 연장(필요시 전 유형), 시험지 확대 복사(시각) 등
- 기타 추가 요청사항 발생 시 장애학생지원센터(279-2434)로 요청