Data-Driven Modeling & Scientific Computation: Methods for Complex Systems & Big Data > 데이터마이닝

I Basic Computations and Visualization
1. MATLAB Introduction
2. Linear Systems
3. Curve Fitting
4. Numerical Differentiation and Integration
5. Basic Optimization
6. Visualization
II Differential and Partial Differential Equations
7. Initial and Boundary Value Problems of Differential Equations144
8. Finite Difference Methods
9. Time and Space Stepping Schemes: Method of Lines
10. Spectral Methods
11. Finite Element Methods
III Computational Methods for Data Analysis
12. Statistical Methods and Their Applications
13. Time-Frequency Analysis: Fourier Transforms and Wavelets
14. Image Processing and Analysis
15. Linear Algebra and Singular Value Decomposition
16. Independent Component Analysis
17. Image Recognition
18. Basics of Compressed Sensing
19. Dimensionality Reduction for Partial Differential Equations
20. Dynamic Mode Decomposition
21. Data Assimilation Methods
22. Equation Free Modeling
IV Scientific Applications
23. Applications of Differential Equations and Boundary Value Problems
24. Quantum Mechanics
25. Applications of Partial Differential Equations
26. Applications of Data Analysis