Foundations of Data Science
Student No.:40
Time:Mon & Wed 13:30-15:05, Sep.17-Dec.12
Instructor:梁鑫Liang Xin  
Place:Conference Room 1, Jin Chun Yuan West Bldg.
Starting Date:2018-9-17
Ending Date:2018-12-12

In the course, we will step into the modern data science by a classical computer science view. Later, random processes, statistics, graphs, optimization, and wavelets will be involved. As a hotspot in the current time, machine learning will also be illustrated. This course is an introduction of the basic topics in data science. Having finished the course, one may have a firm fundamental mathematical base for the advanced study.

Prerequisite: Calculus, Linear Algebra, Probability Theory, Numerical Analysis.

[1] Blum, Hopcroft, and Kannan. Foundations of data science, 2018;
[2] Cady. The data science handbook, John Wiley & Sons, Inc., 2017
[3] Bruce, and Bruce. Practical statistics for data scientists: 50 essential concepts, O'Reilly Media, Inc., 2016.