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An Introduction to Scientific Computing
1. Talking to Computers: Turning Ideas into Instructions
2. Computer Number Representations
3. Randomness and Random Walks
4. Numerical Differentiation and Integration
5. Monte Carlo Methods
6. Matrix Computing, Trial-and-Error Searching and Data Fitting
7. Ordinary Differential Equations
8. An Introduction to Nonlinear Dynamics and Chaos
9. Boundary Value and Eigenvalue Problems
10. Partial Differential Equations
11. More Monte Carlo: The Metropolis Algorithm
12. A Brief Introduction to Monte Carlo Event Generators in Particle Physics
13. Artificial Intelligence and Machine Learning in Physics
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