CSC 430 Introduction to Data Analysis

This course introduces the computational methods for data analysis. Topics include signal processing, frequency filtering, feature extraction, principal component analysis, linear discriminant analysis, statistical tests, and current big data analysis approaches. Students will learn how to apply the data analysis techniques to data scientific research, starting from raw data filtering, going through feature selection and extraction, and finally concluding with data model construction and statistical inference. This course requires the background in probability, statistics, and linear algebra.

Credits

3

Cross Listed Courses

CSC 430, CSC 530, DA 401, DA 501