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Computational Science
Computational Science
34 lessons across 6 topics
1. Numerical Linear Algebra
1
Direct Solvers
2
Eigenvalue Computation
3
Iterative Solvers
4
Matrix Basics
5
Preconditioning
6
Sparse Matrix Techniques
2. Numerical Methods
7
Approximation Theory
8
Interpolation
9
Numerical Differentiation
10
Numerical Integration
11
Root Finding
3. Scientific Programming
12
Numerical Libraries
13
Parallel Programming
14
Performance Optimization
15
Programming Practices
16
Reproducibility
17
Testing And Validation
4. Computational Modeling
18
Deterministic Simulation
19
Model Calibration
20
Model Formulation
21
Multiscale Modeling
22
Stochastic Models
23
Visualization
5. Partial Differential Equations
24
Finite Difference
25
Finite Element
26
Finite Volume
27
Nonlinear Pdes
28
Time Integration
6. Data-Driven Methods
29
Dimensionality Reduction
30
Machine Learning
31
Reduced-order Modeling
32
Regression Methods
33
Statistical Foundations
34
Uncertainty Quantification
