Analytic Combinatorics 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. Part I of this course covers recurrence relations, generating functions, asymptotics, and fundamental structures such as trees, permutations, strings, tries, words, and mappings, in the context of applications to the analysis of algorithms.

Robert Sedgewick is the William O. Baker Professor of Computer Science at Princeton, where he was the founding chair of the Department of Computer Science. He received the Ph.D. degree from Stanford University, in 1975. Prof. Sedgewick also served on the faculty at Brown University and has held visiting research positions at Xerox PARC, Palo Alto, CA, Institute for Defense Analyses, Princeton, NJ, and INRIA, Rocquencourt, France. He is a member of the board of directors of Adobe Systems. Prof. Sedgewick's interests are in analytic combinatorics, algorithm design, the scientific analysis of algorithms, curriculum development, and innovations in the dissemination of knowledge. He has published widely in these areas and is the author of several books.

Math through calculus, CS through algorithms recommended.

This course is based on the textbook An Introduction to the Analysis of Algorithms by Sedgewick and Flajolet. You can find (free) web materials associated with the textbook at http://aofa.cs.princeton.edu/home.

There will be two lectures (80 minutes each) and a problem set each week. There will also be a final exam.

• Does Princeton award credentials or reports regarding my work in this course?

  No certificates, statements of accomplishment, or other credentials will be awarded in connection with this course.