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Syllabus

Infomation of Course

Program Common [공통(상호인정)] Course Type Elective(Graduate) [ 선택(석/박사) ]
Course Code 39.591 Course No CBE591
Section English English
L:L:C(AU) 3:0:3.0(0) Exam time
(classroom)
- Wed: 13:00~15:45
()
Course Title Special Lectures in Chemical and Biomolecular Engineering<Reinforcement Learning for Process Industry> [ 생명화학공학특론<공정산업을 위한 강화학습> ]
Class time
(classroom)
Mon: 14:30~16:00 / (W1)Applied Engineering Bldg. [ (W1)응용공학동 ] (2116)
Wed: 14:30~16:00 / (W1)Applied Engineering Bldg. [ (W1)응용공학동 ] (2116)
Notice

Information of Professor

Name ()
Department ()
Phone
E-Mail

Education4.0 Q

Teaching Style Lecture 100%
Education4.0 Q N

Plan of Lecture

Syllabus File CBE591_JLee_22F.pdf
Syllabus URL
Summary of Lecture The first half of the course will cover general machine learning concepts and tools, esp. regression and time-series modeling. The second half will focus on reinforcement learning, a branch of machine learning, is a technique for deriving an optimal decision policy through repeated (simulation or real) databased refinement. This course introduces the basic theories and methodologies of machine learning / reinforcement learning and explores how the technique can best be utilized in process industry applications, e.g., monitoring, prediction, planning, scheduling, and control.
Material for Teaching
Evaluation Criteria
Lecture Schedule
Memo