校際選修

115-1 選課時程

進行中

  • 初選第一階段 6/15/2026
  • 初選第二階段 6/22/2026
  • 校際選修 8/24/2026
  • 初選第三階段 8/31/2026
  • 開學後加退選 9/7/2026
  • 逾期加退選 9/21/2026
選課資源

生醫資訊深度學習

Deep Learning in Biomedical Informatics

學期
112-2
學分
3 學分
當期課號
535523
永久課號
CSIC30082
開課單位
資訊科學與工程研究所
授課教師
魏群樹
校區
光復
類別
選修
上課時間表
週五
3
10:10–11:00
生醫資訊深度學習
EC329
2 節連堂
4
11:10–12:00

* 根據陽明交大上課時間表所列

概述

This course offers a comprehensive understanding of fundamental concepts, hands-on experience, and the ability to critically review and propose research in the field of deep learning for biomedical data analysis, with a focus on EEG data analysis. Objectives: - Understanding fundamental machine learning and deep learning (ML/DL) - Exploring EEG datasets and related works - Developing skills in conducting a comprehensive literature review in the field of biomedical data analysis - Ability to effectively present methodologies, findings, and insights obtained during laboratory exercises - Skills to draft research proposals in the domain of deep learning for biomedical data analysis

先修科目

Math (calculus, linear algebra, etc) Fundamental machine learning/deep learning Basic Python programming

教學方式

TA: Yi-Ning Huang (jg930432@gmail.com) - All registered students and waitlist students should attend the first class. Limited additional enrollment will be available at the end of the first class. Students fail to participate in the first meeting may be withdrawn from the class as a 'no show'. - No show in class may lead to loss in grades. ***** Course operation may be subject to change due to unforeseen causes. *****

評分方式

Lab: 25% Paper review: 20% Proposal: 30% Participation: 25%

週次計畫
週次主題
第 1 週Course introduction
第 2 週Fundamental ML/DL
第 3 週Fundamental ML/DL
第 4 週Fundamental ML/DL
第 5 週EEG datasets and related works
第 6 週Lab: EEG analysis with explainable deep neural networks
第 7 週No class (holiday)
第 8 週EEG datasets and related works
第 9 週Lab demo
第 10 週Proposal drafting
第 11 週Paper review
第 12 週Paper review
第 13 週Paper review
第 14 週Invited talk
第 15 週Proposal presentation
第 16 週Proposal presentation
教科書

Literature reading; Online resources.

Office Hours
地點
EC240, Engineering Building III, Guang-Fu Campus
時間
By appointment.
聯絡方式
Chun-Shu Wei (wei@nycu.edu.tw)