Course Outline: Big Data Analysis in Economics at Chiang Mai University
Dr. Woraphon Yamaka offers a comprehensive course on Big Data Analysis in Economics at the Faculty of Economics, Chiang Mai University. The course covers topics such as Data Science, Econometrics, Machine Learning, R programming, Data Visualization, Symbolic Data Analysis, Machine Learning Modeling, Deep Learning, and Text Mining. Assessment includes academic knowledge evaluation, homework, final exam, and coding report. Required texts include resources on R, ggplot2, and advanced statistical programming. PowerPoint presentations are available on Dr. Woraphon Yamaka's blog.
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DR. WORAPHON YAMAKA COURSE OUTLINE BIG DATA ANALYSIS IN ECONOMICS FACULTY OF ECONOMICS CHIANG MAI UNIVERSITY WYAMAKA.WORDPRESS. COM
Course Content No. of (Lect. hours or Lab ) 1. Introduction and Data Science, Econometrics and Machine learning 3 2. Introduction of R programming 6 3. Data visualization 3 4. Symbolic data analysis 3 5. Machine learning and Deep learning modeling 6 6. Text mining 6 Total 45
ASSESSMENT OF THE ASSIGNED TASKS Evaluation Assessment of academic knowledge Homework percent30 TBA Final percent50 TBA Assessment of the assigned tasks Coding report percent20
Material Power point presentations are provided in my blog wyamaka.wordpress.com
REQUIRED TEXT Horton, N. J., & Kleinman, K. (2015). Using R and RStudio for data management, statistical analysis, and graphics. CRC Press. Teutonico, D. (2015). ggplot2 Essentials. Packt Publishing Ltd.. Wiley, M., & Wiley, J. F. (2019). Advanced R Statistical Programming and Data Models: Analysis, Machine Learning, and Visualization. Apress.
