人工智慧
Artificial Intelligence
| 節 | 週二 |
|---|---|
5 13:20–14:10 | 人工智慧 M301 3 節連堂 |
6 14:20–15:10 | |
7 15:30–16:20 |
* 根據陽明交大上課時間表所列
This course aims to teach the basic theory, application, and implementation skills of artificial intelligence technology, covering machine learning and deep learning and their applications in management science. Students will learn how to develop and deploy AI-based systems and explore real-world applications of AI technology.
No course prerequisites are needed to enroll in this course. 第一週務必到課聆聽課程介紹與相關規定,若未到課將會從修課名單中被退選或無法加簽.
(a) Teaching methods include lectures, presentations, implementations, practical exercises, and discussions. (b) The E3 digital learning platform will be utilized to support the course. (c) Some sessions will be conducted using asynchronous online learning.
(a) Assignments: 60% (b) Programming demo and presentation: 20% (c) Paper presentation: 20%
| 週次 | 主題 |
|---|---|
| 第 1 週 | Course Introduction & AI Overview |
| 第 2 週 | AI Research |
| 第 3 週 | Introduction to AI/ML/DL |
| 第 4 週 | Anaconda Environment & Python Programming |
| 第 5 週 | AI建模基礎/過度擬合/重新取樣 ML in Python |
| 第 6 週 | 關聯規則 / Python實作報告 |
| 第 7 週 | AI Guest Lecture 1 |
| 第 8 週 | 群集分析 / Python實作報告 |
| 第 9 週 | 決策樹分析 / Python實作報告 |
| 第 10 週 | KNN&SVM / Python實作報告 |
| 第 11 週 | 類神經網路&深度學習 |
| 第 12 週 | Regression, Classification Multilayer Perceptron (MLP) |
| 第 13 週 | Computer Vision (CV) Convolutional Neural Networks (CNN) |
| 第 14 週 | Natural Language Processing (NLP) Recurrent Neural Networks (RNN) |
| 第 15 週 | 期末論文報告1 |
| 第 16 週 | 期末論文報告2 |
1. Lecturer-prepared teaching slides materials 2. 新一代 Keras 3.x 重磅回歸:跨 TensorFlow 與 PyTorch 建構 Transformer、CNN、RNN、LSTM 深度學習模型, 陳會安, 旗標, 2024. 3. 從零開始學Python程式設計, 李馨, 博碩文化, 2024.
- 地點
- M308
- 時間
- 未定
- 聯絡方式