高等智慧資料分析演算法
Advanced Intelligent Data Analysis Algorithm
| 節 | 週三 |
|---|---|
1 08:00–08:50 | 高等智慧資料分析演算法 M301 2 節連堂 |
2 09:00–09:50 |
* 根據陽明交大上課時間表所列
This course provides students with in-depth knowledge and skills in intelligent algorithms used for data analysis. This course covers advanced techniques emphasizing their application to real-world data problems. In addition to practical implementations, students will be required to engage with a wide range of advanced academic journal articles and conference papers. These readings will be the foundation for in-class discussions, encouraging students to critically evaluate cutting-edge research and its impact on data analysis. Students will explore how these algorithms can be adapted and implemented in various fields, enabling them to extract meaningful insights from complex datasets. The course also emphasizes hands-on experience, requiring students to apply these algorithms to real data sets using appropriate programming tools.
It is recommended that students have prior experience with Python programming, knowledge of database design, and have completed courses related to data analysis or machine learning algorithms. This class is ONLY for students in the Department of Management Science
(a) Teaching methods include lectures, presentations, case studies, 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) Course participation and assignments (10%) (b) Research paper presentations & reports (30%) (c) Topic presentation & reports (20%) (d) Programming implementation (20%) (e) Midterm and Exam (20%)
| 週次 | 主題 |
|---|---|
| 第 1 週 | Course Introduction and Overview of Intelligent Data Analysis (IDA) |
| 第 2 週 | Fundamentals of IDA and Data Preprocessing Topic presentation 1 / Paper discussion 1 |
| 第 3 週 | Supervised Learning Algorithms Overview 1 Topic presentation 2 / Paper discussion 2 |
| 第 4 週 | Supervised Learning Algorithms Overview 2 Topic presentation 3 / Paper discussion 3 |
| 第 5 週 | Unsupervised Learning and Clustering Algorithms Overview 1 Topic presentation 4 / Paper discussion 4 |
| 第 6 週 | Unsupervised Learning and Clustering Algorithms Overview 2 Topic presentation 5 / Paper discussion 5 |
| 第 7 週 | IDA Programming Implementation 1 Midterm |
| 第 8 週 | Guest Lecture Invitation |
| 第 9 週 | Time Series Analysis and Forecasting Topic presentation 6 / Paper discussion 6 |
| 第 10 週 | Deep Learning and Applications 1 Topic presentation 7 / Paper discussion 7 |
| 第 11 週 | Deep Learning and Applications 2 Topic presentation 8 / Paper discussion 8 |
| 第 12 週 | Natural Language Processing and Text Mining 1 Topic presentation 9 / Paper discussion 9 |
| 第 13 週 | Natural Language Processing and Text Mining 2 Topic presentation 10 / Paper discussion 10 |
| 第 14 週 | IDA Advanced Programming Implementation 2 |
| 第 15 週 | Guest Lecture Invitation |
| 第 16 週 | Final Project Presentations and Discussions Final Exam |
1. Lecturer-prepared teaching slides and materials 2. Selected academic journal and conference papers
- 地點
- M308
- 時間
- Not determined
- 聯絡方式