Resources

Code

• For all supplementary code: M260 github (Fall 2020)

General

• F20 Syllabus (PDF)
• Getting started (python) (PDF)
• Guidelines for coding (PDF)
• Project guide (PDF)

Lecture Notes (main)

• Intro (overview) (PDF)
• Intro (more python) (PDF)
• Intro (under the hood) (PDF)
• Intro (numerics and algorithms) (PDF)


• Linear systems (Gaussian elimination) (PDF)
• Classes in python (PDF)
• Data structures (recursion, stacks, trees) (PDF)
• Data structures (dictionaries, binary trees) (PDF)


• Application: PageRank (Markov chains, the power method) (PDF)
• Solving ODEs numerically (Euler, RK methods, systems) (PDF)
• Application: Signal processing (the fast Fourier transform) (PDF)
• Application: data fitting (least squares, gradient descent) (PDF)
• Finite differences - PDEs, method of lines (PDF)

Lecture Notes (additional)

• Python notes: error handling (PDF)
• Python: numpy intro (PDF)
• Python: subclasses, decorators (PDF)
• Banded systems (finite differences) (PDF)
• More on ODEs (stiff equations) (PDF)

Homework

• Homework 1 (PDF)
• Homework 2 (PDF)
• Homework 3 (PDF)
• Homework 4 (PDF)
• Homework 5 (PDF)
• Homework 6 (PDF)
• Homework 7 (PDF)
• Homework 8 (PDF)
• Homework 9 (PDF)
• Homework 10 (PDF)