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1. Introduction to programming in Python 1
1.1. Jupyter Notebooks and Python Basics
1.2. Functions in Python
1.3. Python program flow control
2. Introduction to programming in Python 2
2.1. Scientific Computing in Python with Numpy
2.2. Data in Python: Loading, Plotting, and Fitting
2.3. Developing and testing algorithms
2.4. Additional Programming Concepts in Python - Optional
2.5. Good coding practices
3. Numerical Differentiation
4. Numerical Integration
5. Root finding
6. Linear algebra
7. TN2513 Lecture 7: Basics of the Discrete Fourier Transform
8. Applications of the Fourier Transform
9. Random numbers
10. Monte Carlo simulations
11. Ordinary Differential Equations Part 1
12. Ordinary Differential Equations Part 2
13. Partial Differential Equations 1: Boundary Value Problems
14. TN2513 Lecture 14: Initial Value Problems with PDEs
Index
