Prospective Students

Below are the recommended prerequisite (but not strictly required) courses for those who consider the graduate student positions in our lab.

Courses in boldface are for master's program (including integrated program) applicants.

In addition to them, Ph.D. program applicants are encouraged to take courses or equivalent marked with asterisks (*) before application.

아래의 교과목은 LST 연구실에 연구하기 위해 도움이 되는 학부 교과목 리스트 입니다.

석사과정 지원자(통합과정 포함)진한색, 박사과정 지원자는 진한색 교과목과 더불어 별표가 있는 교과목을 지원하기 전에 이수하기를 권장합니다(강제사항은 아님).

Courses in IME Department

  • IMEN242 Introduction to Experimental Design (실험계획개론)*

  • IMEN260 Operations Research I (경영과학I)

  • IMEN266 Operations Research II (경영과학II)

  • IMEN272 Probability and Statistics for Engineers (공학기초통계)

  • IMEN281 Information System Technology (for programming) (정보시스템기술)

  • IMEN371 Quality Management (품질경영)

  • IMEN461 Mathematical Programming (수리계획)*

  • IMEN472 Statistical Data Mining (통계적데이터마이닝)

  • IMEN486 Introduction to Financial Engineering (금융공학개론)

Courses in MATH Department

  • MATH200 Differential Equations (미분방정식)*

  • MATH203 Applied Linear Algebra (응용선형대수)

  • MATH311 Analysis I (Real Analysis I) (해석학I)*

  • MATH312 Analysis II (Real Analysis II) (해석학II)*

  • MATH351 Introduction to Numerical Analysis(수치해석개론)*

  • MATH412 Introduction to Ordinary Differential Equations (상미분방정식론)

  • MATH413 Introduction to Partial Differential Equations (편미분방정식론)

  • MATH431 Introduction to Probability Theory (확률개론)*

Courses in CSE Department

  • CSED232 Object Oriented Programming (객체지향프로그래밍)

  • CSED233 Data Structure (자료구조)

  • CSED331 Algorithms (알고리즘)*

  • CSED442 Artificial Intelligence (인공지능)*