Music Information Retrieval with Deep Learning
딥러닝 기반 음악정보학
education program·graduate course·unknown·also: GITA397
Two-credit graduate curriculum course implementing deep-learning tasks across music classification, tagging, source separation, transcription, symbolic generation and sound synthesis.
Verified facts
| Official site | https://scc.sogang.ac.kr/gsinfo/gsinfo04_3.html ↗ |
|---|---|
| Geography | Seoul, South Korea |
| course code | GITA397 |
| price | Included in university tuition; course-specific amount not disclosed |
| title | GITA397 딥러닝 기반 음악정보학 |
| format | unknown |
| topics | music classification; music tagging; source separation; automatic transcription; symbolic music generation; sound synthesis |
| duration | 2 credits |
| end date | unknown |
| language | Korean; English title supplied by provider |
| location | Sogang University, Seoul |
| provider | Sogang University Graduate School of Information & Technology / AI·SW Graduate School |
| recurrence | Current curriculum; next taught semester not published |
| start date | unknown |
| instructors | unknown |
| program type | graduate course |
| prerequisites | Graduate programme enrolment; technical prerequisites not stated |
| program state | active_schedule_unverified |
| target audience | AI·SW graduate students; data-science and AI graduate students |
| learning outcomes | Implement representative MIR tasks with deep learning; understand music-data characteristics and suitable preprocessing |
| application deadline | Institutional course registration |
| credential or outcome | 2 graduate credits |
| scholarship and funding | No course-specific funding disclosed |
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