Advanced Linear Algebra (CSE7513) β Fall 2026
Kyung Hee University Β· School of Computing (Graduate) Β· Mon & Wed 13:30β14:50 Β· Room μ 103 Β· Instructor: Byounghyun Yoo
One principle β Prepare with AI. Prove it in person, without devices.
Learn on your own with AI as a tutor; prove your understanding live β in presentations and exams β with no devices.Two intents
1.
Learn β build the ability to break into an unfamiliar topic on your own, with an AI agent as your tutor.
2.
Teach β every student teaches one 18.065 lecture (flipped learning).
Core materials
β’
MIT OCW 18.065 (Strang) β required pre-class videos + textbook Linear Algebra and Learning from Data (2019)
β’
K-MOOC βLinear Algebra for Deep Learningβ (Pusan Natβl Univ.) β Korean support
β’
Korean translation β sections map 1:1 with the book (I.8 β 1.8)
Quick links
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At a glance
Item | Detail |
Classes | Twice weekly Γ 80 min, 30 sessions (15 weeks) |
Presentations | One per student, starting 9/9 |
Exams | Midterm 10/21 Β· Final 12/16 (AI-free written + AI-use written interview) |
English | not graded |
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1.
Learn β AI νν°μ λμμΌλ‘ λ―μ μ£Όμ λ₯Ό μ€μ€λ‘ λ«λ λ₯λ ₯μ κΈ°λ₯Έλ€.
2.
Teach β νμ μ μμ΄ 18.065 κ°μ ν νΈμ©μ μ§μ κ°λ₯΄μΉλ€(ν립λ¬λ).
ν΅μ¬ μλ£
β’
MIT OCW 18.065 (Strang) β νμ μ¬μ νμ΅ μμ + κ΅μ¬ Linear Algebra and Learning from Data (2019)
β’
K-MOOC γλ₯λ¬λμ μν μ νλμνγ(λΆμ°λ) β νκ΅μ΄ 보쑰
β’
νλΉ λ²μμ β μμμ μ 1:1 (I.8 β 1.8)
λΉ λ₯Έ μ΄λ
β’
νλμ
νλͺ© | λ΄μ© |
μμ
| μ£Ό 2ν Γ 80λΆ, μ΄ 30μΈμ
(15μ£Ό) |
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