School of Economics and Management
Beihang University

General information

  • Credits: 2 credits
  • Lecturer: Yanfei Kang
  • Language: Taught in Chinese. Materials are in English.
  • Computer language: R
  • Reception hours: Questions concerned with this course can be asked during or after each lecture or via email.
  • Lecture notes: available on on


Unit objectives

The process of statistical modeling.

Unit objectives

  1. Learn R programming for data science;
  2. Learn optimization and simulation tools;
  3. Develop computational linear algebra techniques, such as eigenanalysis and singular value decomposition and their applications.


  • Assignments (labs): 40%
  • Final exam: 60%

About assignments

  1. Subject of your email: “SC2019Lab-N-Name-StudentID”.
  2. Email attachments: R script named as “SC2019Lab-N-Name-StudentID.R”.
  3. Pls let me know who you are.
  4. Pls write a decent email.

Course contents

  • R for data science
    • R basics
    • Managing data frames with the dplyr package
    • Control structures and functions
    • Dealing with text data
    • Debugging and Profiling R code
  • Optimization
    • Newton’s method
    • Quasi-Newton methods
    • Derivative free methods
  • Computational Linear Algebra
    • Eigenanalysis
    • Singular value decomposition (SVD)
    • Basic applications of SVD
    • Numerical algorithms for eigenanalysis
    • Image recognition based SVD
    • SVD in text mining
  • Review