Program Overview
Master of Artificial Intelligence
Master's Program in AI Convergence Engineering
Master of Science in AI Convergence Engineering
Program Overview
Course Introduction
In recent times, companies are entering an era where new innovations are crucial for survival. In response, they are striving to innovate various digital services through the convergence of industry and IT. AI convergence involves combining AI technology with other fields to create new value. For instance, in the medical field, AI technology can be employed for disease diagnosis and drug development. Additionally, AI technology can be applied in self-driving cars, smart homes, and smart cities to introduce new services and business models.
The significance of AI convergence is challenging to encapsulate in a single phrase, but it can be articulated through three key aspects:
1. Creating New Value: By integrating AI technology with other fields, novel business models and services can be developed.
2. Increasing Productivity: AI technology can enhance productivity. For example, in an automated production system, AI can be utilized to classify defective products or predict failures.
3. Problem-solving: AI technology can address various challenges. For instance, solutions for environmental or energy-related issues can be identified.
Therefore, the AI convergence department aims to cultivate "AI convergence professionals" capable of understanding AI-based digital business, a pivotal role in diverse fields both now and in the future. They are equipped to plan and execute new businesses.
Course Features
The graduate curriculum of the AI convergence department comprises the following components
- Basic Subjects: In the AI Convergence Department, students complete fundamental courses in mathematics, statistics, and computer science, acquiring foundational knowledge of AI technology.
- AI Core Technology: The department provides education on essential AI technologies such as machine learning, deep learning, natural language processing, and computer vision, encompassing both theoretical understanding and practical application.
- AI Convergence Field: Students learn how to create new services and business models by merging AI technology with other fields, developing the ability to apply AI across various domains.
- Projects: The AI convergence department undertakes projects addressing real-world issues encountered in industrial settings. This ensures the development of practical skills alongside theoretical education.
- Ethics and Laws: Given that AI technology can raise legal and ethical concerns, the curriculum includes training on AI ethics and laws.
교수진 소개
홍승필
주임교수
KAIST 박사
- 현) 서울과학종합대학원대학교 교수
- 전) ㈜한컴위드 대표
- 전) 성신여자대학교 교수
- 전) ㈜LG CNS 책임연구원
민경식 박사
경영보안전공, KISA
학력
- 일본 메이지대학교 대학원 경제학박사
- 일본 메이지대학교 대학원 경제학 석사
경력
- 한국인터넷진흥원 팀장/연구위원
- 일본 하이퍼네트워크사회연구소 공동연구원
- 한국인터넷정책학회 이사
- 서울시 블록체인 자문위원
- 경상남도 블록체인 자문위원
- 우정정보사업센터 블록체인 지문위원
연구분야
- ICT분야 경제성분석, 보안정책, 블록체인, 메타버스 보안 등
김관하
법무법인 이제, 변호사
학력
- 서울대학교 법과대학 졸업 (법학사, 1998)
- 사법연수원 수료 (30기, 2001)
- USC Law School (Visiting, 2010-2011)
경력
- 육군 법무관 (2001. 4.-2004. 3.)
- 김∙장 법률사무소 (2004. 4.-2015. 1.)
- 법무법인 이제 구성원-파트너 변호사 (2015. 2.-현재)
- 서울지방노동위원회 심판담당 공익위원 (2016. 4.-현재)
분야
- 인사노무 (중대재해처벌, 직장내 괴롭힘법등)
- 대한민국 사법시험 합격 (제40회, 1998)
- 2016년/2017년 highly recommended lawyer으로 선정(Legal Times, 인사노무)
- 2019년/2020년/2021년 「Leading lawyer」로 선정(Legal Times, 인사노무)
* 향후 KISA 전문가, 대학교수 추가 예정
