資訊視覺化的目的在於透過視覺化的方式呈現資料,協助使用者有效地去理解資料的本質與特性。本課程透過問題導向切入資訊視覺化研究,優先思考資料與任務的抽象,然後選擇最合適的表現方式。最後才考量演算法的效率問題。
- 教師: 紀 明德
Hierarchical Linear Modeling
階層線性模型分析
- 教師: 游 琇婷
動態系統是可用以描繪演化現象的數學方法之一。在許多不同領域如物理,化學, 生態, 生物, 工程, 腦科學和經濟學上都有重大應用。
- 教師: 曾 睿彬
本課程邀請專家學者演講,讓學生可以接觸數學相關領域的研究主題。
- 教師: 曾 睿彬
This course aims to introduce data science from a pragmatic, practice-oriented viewpoint. Students will learn concepts, R programming language and tools they need to deal with various facets of data science practice, including data integration, exploratory data analysis, predictive modeling, evaluation and effective visual communication. By the end of the course they will be able to apply data science techniques on their own research topics.
This course is designed to provide a substantial exposure to the C programming language in a Unix environment for students with basic programming experience. Advanced features of the C language that are emphasized include structs and unions, File I/O, dynamic memory allocation (malloc and free), pointers, pointer arithmetic, and casting. Data structures that are emphasized include linked lists, queue, and stack. Students will develop a sense of proper programming style in C, and will be exposed to cross-platform portability issues. Students will also learn to use several Unix tools such as gdb, emacs/vi, svn/git, make, grep, diff etc. to assist them in the design, testing and debugging of their programs. In addition, students will learn some basic shell scripting, and Perl/Python to solve simple problems.
課程設計主要參考蔡銘峰老師之前授課,感謝!