Program | Common [공통(상호인정)] | Course Type | Elective(Graduate) [ 선택(석/박사) ] |
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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
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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) |
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Lecture 100% |
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Education4.0 Q | N |
Syllabus File | CBE591_JLee_22F.pdf |
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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. |
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