| Relevance of Course Objectives and Core Learning Outcomes(%) |
Teaching and Assessment Methods for Course Objectives |
| Course Objectives |
Competency Indicators |
Ratio(%) |
Teaching Methods |
Assessment Methods |
| to teach students the data processing and data mining skill. |
|
|
| Lecturing |
| Discussion |
| Exercises |
| topic Discussion/Production |
|
| Other |
| Study Outcome |
| Attendance |
|
| Course Content and Homework/Schedule/Tests Schedule |
| Week |
Course Content |
| Week 1 |
Introduction to biological data. |
| Week 2 |
Data structure and pattern. |
| Week 3 |
Data sampling, mining and modeling. |
| Week 4 |
Data validation and virtualization. |
| Week 5 |
Data pattern recognition. |
| Week 6 |
Large-scale data (big-data) and image data processing. |
| Week 7 |
Introduction to R. |
| Week 8 |
R programing for large-scale data analysis. |
| Week 9 |
R programing for data visualization. |
| Week 10 |
Introduction to data dimension reduction. |
| Week 11 |
Introduction to data similarity. |
| Week 12 |
Introduction to data clustering. |
| Week 13 |
Introduction to Artificial Intelligence (AI) and machine learning |
| Week 14 |
Supervised machine learning. |
| Week 15 |
Unsupervised machine learning. |
| Week 16 |
Application of Neuro Network and Deep Learning in biological modeling. Discussion and Review. |
| Week 17 |
Self-study - I: Practice on case study of causality analysis between factors. |
| Week 18 |
Self-study - II: Practice on case study of explanatory machine learning. |
|
| Evaluation |
| participation rate, homeworks |
| Textbook & other References |
1. Witten, I. H., E. Frank, M. A. Hall, and C. J. Pal. 2016. Data Mining: Practical machine learning tools and techniques. Morgan Kaufmann.
2. Heath, L. S., and N. Ramakrishnan. 2010. Problem Solving Handbook in Computational Biology and Bioinformatics. Springer Science & Business Media.
3. Robert Gentleman. R Programming for Bioinformatics. 2008. CRC Computer Science & Data Analysis
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| Teaching Aids & Teacher's Website |
|
| Office Hours |
| Working hour or by appointment. |
| Sustainable Development Goals, SDGs |
| include experience courses：N |
|