| Instructor | Hao-Wen (Herman) Dong (ude.hcimu@gnodwh) |
| Room | Moore 376 (Davis) or Zoom |
| Days & times | 1:30–3pm, Mondays & Wednesdays |
| Office hours | By appointment |
[Gradescope] [Last year’s course website]
An introduction to the emerging field of AI music. This course introduces students to AI’s applications in music from analysis, creation, retrieval to processing. Example topics include music transcription, optical music recognition, music source separation, automatic music composition, music synthesis, music recommendation and auto-mixing. Students will gain hands-on experience on using AI tools through open-ended assignments and a final project on a relevant topic of their choice. Prior coding experience is recommended.
This course counts towards the PAT Minor (Upper Level Elective), CS-Eng/DS-Eng (Flex Tech Elective), and MIDAS GDSC (Electives) programs.
| Week | Date | Lecture | Recording | Assignment |
|---|---|---|---|---|
| 1 | Aug 31 | Introduction | ||
| Background | ||||
| Sep 2 | ├ AI & ML Fundamentals | |||
| 2 | ├ |
|||
| Sep 9 | ├ AI & Music | |||
| 3 | Sep 14 | ├ Music Processing Fundamentals & PA 1 | HW 1 due | |
| Sep 16 | ├ Audio Processing Fundamentals | |||
| 4 | Sep 21 | ├ PA 2 Walkthrough & Catch-up | ||
| Sep 23 | ├ Deep Learning Fundamentals | PA 1 due | ||
| 5 | Sep 28 | ├ Deep Learning Fundamentals II | ||
| Sep 30 | └ Buffer | |||
| Analysis | ||||
| 6 | Oct 5 | ├ Source Separation | PA 2 due | |
| Oct 7 | ├ Convolutional Neural Networks & PA 3 | |||
| 7 | Oct 12 | ├ Music Analysis | ||
| Oct 14 | └ Music Classification & PA 4 | |||
| 8 | ||||
| Creation | ||||
| Oct 21 | ├ Language-based Music Generation | HW 2 due | ||
| 9 | Oct 26 | ├ Piano Roll-based Music Generation | ||
| Oct 28 | ├ Audio-domain Music Generation | PA 3 due | ||
| 10 | Nov 2 | └ Latent-based Music Generation | ||
| Nov 4 | Project Pitch | |||
| 11 | PA 4 due | |||
| 12 | Nov 16 | Buffer | HW 3 due | |
| Retrieval & Processing | ||||
| Nov 18 | ├ Music Production & Editing | |||
| 13 | Nov 23 | ├ Buffer | ||
| ├ |
HW 4 due | |||
| 14 | Nov 30 | └ Music Search & Recommendation | ||
| Dec 2 | Discussions, Challenges & Opportunities | |||
| 15 | Dec 7 | Buffer | ||
| Dec 9 | Project Presentation |
All slides are licensed under CC BY 4.0.
| Homework | Due |
|---|---|
| HW 1: Real or Fake!? | TBD |
| HW 2: Source Separation | TBD |
| HW 3: AI Song Contest 2026 | TBD |
| HW 4: AI Music Tools | TBD |
| Programming Assignment | Due |
|---|---|
| PA 1: Symbolic Music Processing | TBD |
| PA 2: Spectral Analysis | TBD |
| PA 3: Source Separation | TBD |
| PA 4: Musical Note Classification | TBD |
| Milestone | Due |
|---|---|
| Pitch | Nov 4 |
| Presentation | Dec 9 |
| Report | Dec 16 |
All grading and regrade requests will be handled on Gradescope.
The final grading scale is as follows.
| A+ | 97+ | B+ | 87–89 | C+ | 77–79 | D+ | 67–69 | F | <60 |
| A | 93–96 | B | 83–86 | C | 73–76 | D | 63–66 | ||
| A− | 90–92 | B− | 80–82 | C− | 70–72 | D− | 60–62 |
The University of Michigan recognizes disability as an integral part of diversity and is committed to creating an inclusive and equitable educational environment for students with disabilities. Students who are experiencing a disability-related barrier should contact Services for Students with Disabilities ((734) 763-3000 or ssdoffice@umich.edu). For students who are connected with SSD, accommodation requests can be made in Accommodate. If you have any questions or concerns please contact your SSD Coordinator or visit SSD’s Current Student webpage. SSD considers aspects of the course design, course learning objects and the individual academic and course barriers experienced by the student. Further conversation with SSD, instructors, and the student may be warranted to ensure an accessible course experience.
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