1. CS 322 Week 2
As professional SE, always think about complexity reduction
Stream data processing: big data using diff alg/data struc
space O(1)
Role of math/stats (linear alg: eigen vector/value—google pagerank, calculus: Taylor series: Machine learning: gradient descent/save training sample, probability, Bayesian stats/subjective/belief-classic/frequentist, keep updating belief based on new evidence, information: -log(p), optimization/calculus: nullifying 1st derivative etc.) in problem modeling and solving in software engineering

2. CS 322 week 2
Mathematical/complexity modeling: objective function and optimization behind un/robustness of mean and median; problem analysis, objective function formulation; calculus + stats reasoning to justify
Gold standard of science: testing (randomized testing, one major component of software engineering). Stat reasoning typical for algorithm design and problem solving
Sw measurements: efficiency (space+time complexity), user-friendly: to ordinary user, understandability: to peer programmers (kolmogorov)