PGD01C05
Core theory
4 credits
5 modules · 23 topics
Computational Methods for Data Science
Computational tools applied to data: statistics, Fourier and wavelet analysis, image processing, SVD/PCA/ICA, image recognition and compressed sensing.
Course outcomes
Understand different statistical methods and their applications.
Have an idea about time-frequency analysis.
Learn Principal Component Analysis.
Modules
References
Yeliz Karaca & Carlo Cattani, Computational Methods for Data Analysis, O'Reilly, 2018.
Siegmund Brandt, Data Analysis: Statistical and Computational Methods for Scientists and Engineers, Springer, 2017.
Narayana, Ranjan & Tyagi, Basic Computational Techniques for Data Analysis, Sage, 2021.