Analysis of Algorithms aims to enable precise quantitative predictions of the properties of large combinatorial structures. The theory has emerged over recent decades as essential both for the scientific analysis of algorithms in computer science and for the study of scientific models in many other disciplines, including probability theory, statistical physics, computational biology and information theory.
- Functions and inverse functions
- Limits, derivatives, partial derivatives, and chain rule
- Integrals and multiple integrals, changing the order of differentiation and integration
- Taylor series approximations
- Newton’s method
PART OF THE WHARTON MBA FOUNDATION SERIES
This course is part of the Wharton MBA foundation series in the MOOC format. It is taught by three of Wharton's top faculty in the marketing department, which is consistently ranked as the #1 marketing department in the world. This course features on-location videos and debates between the three professors.