Introduction to Enumerative Combinatorics (Coursera)

Introduction to Enumerative Combinatorics (Coursera)

Enumerative combinatorics deals with finite sets and their cardinalities. In other words, a typical problem of enumerative combinatorics is to find the number of ways a certain pattern can be formed. In the first part of our course we will be dealing with elementary combinatorial objects and notions: permutations, combinations, compositions, Fibonacci and Catalan numbers etc. In the second part of the course we introduce the notion of generating functions and use it to study recurrence relations and partition numbers.

Class Deals by MOOC List - Click here and see Coursera's Active Discounts, Deals, and Promo Codes.

The course is mostly self-contained. However, some acquaintance with basic linear algebra and analysis (including Taylor series expansion) may be very helpful.

Syllabus

WEEK 1
Introduction
Permutations and binomial coefficients
In this introductory lecture we discuss fundamental combinatorial constructions: we will see how to compute the number of words of fixed length in a given alphabet, the number of permutations of a finite set and the number of subsets with a given number of elements in a finite set. The latter numbers are called binomial coefficients; we will see how they appear in various combinatorial problems in this and forthcoming lectures. As an application of combinatorial methods, we also give a combinatorial proof of Fermat's little theorem.

WEEK 2
Binomial coefficients, continued. Inclusion and exclusion formula.
In the first part of this lecture we will see more applications of binomial coefficients, in particular, their appearance in counting multisets. The second part is devoted to the principle of inclusion and exclusion: a technique which allows us to find the number of elements in the union of several sets, given the cardinalities of all of their intersections. We discuss its applications to various combinatorial problem, including the computation of the number of permutations without fixed points (the derangement problem).

WEEK 3
Linear recurrences. The Fibonacci sequence
We start with a well-known "rabbit problem", which dates back to Fibonacci. Using the Fibonacci sequence as our main example, we discuss a general method of solving linear recurrences with constant coefficients.

WEEK 4
A nonlinear recurrence: many faces of Catalan numbers
In this lecture we introduce Catalan numbers and discuss several ways to define them: via triangulations of a polygon, Dyck paths and binary trees. We also prove an explicit formula for Catalan numbers.

WEEK 5
Generating functions: a unified approach to combinatorial problems. Solving linear recurrences
We introduce the central notion of our course, the notion of a generating function. We start with studying properties of formal power series and then apply the machinery of generating functions to solving linear recurrence relations.

WEEK 6
Generating functions, continued. Generating function of the Catalan sequence
In this lecture we discuss further properties of formal power series. In particular, we prove an analogue of the binomial theorem for an arbitrary rational exponent. We apply this technique to computing the generating function of the sequence of Catalan numbers.

WEEK 7
Partitions. Euler’s generating function for partitions and pentagonal formula
In this lecture we introduce partitions, i.e. the number of ways to present a given integer as a sum of ordered integer summands. There is no closed formula for the number of partitions; however, it is possible to compute their generating function. We study the properties of this generating function, including the famous Pentagonal theorem, due to Leonhard Euler.

WEEK 8
Gaussian binomial coefficients. “Quantum” versions of combinatorial identities
Our final lecture is devoted to the so-called "q-analogues" of various combinatorial notions and identities. As a general principle, we replace identities with numbers by identities with polynomials in a certain variable, usually denoted by q, that return the original statement as q tends to 1. This approach turns out to be extremely useful in various branches of mathematics, from number theory to representation theory.

Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Aléatoire : une introduction aux probabilités - Partie 1 (Coursera) Coursera
École Polytechnique

Aléatoire : une introduction aux probabilités - Partie 1 (Coursera)

Ce cours d'introduction aux probabilités a la même contenu que le cours de tronc commun de première année de l'École polytechnique donné par Sylvie Méléard. Le cours introduit graduellement la notion de variable aléatoire et culmine avec la loi des grands nombres et le théorème de la limite centrale. Les notions mathématiques nécessaires sont introduites au fil du cours et de nombreux exercices corrigés sont proposés.

Oct 5th 2026
5-12 Weeks
Data Science Math Skills (Coursera) Coursera
Duke University

Data Science Math Skills (Coursera)

Data science courses contain math—no avoiding that! This course is designed to teach learners the basic math you will need in order to be successful in almost any data science math course and was created for learners who have basic math skills but may not have taken algebra or pre-calculus. Data Science Math Skills introduces the core math that data science is built upon, with no extra complexity, introducing unfamiliar ideas and math symbols one-at-a-time.

Sep 24th 2026
4 Weeks
Single Variable Calculus (Coursera) Coursera
University of Pennsylvania

Single Variable Calculus (Coursera)

Calculus is one of the grandest achievements of human thought, explaining everything from planetary orbits to the optimal size of a city to the periodicity of a heartbeat. This brisk course covers the core ideas of single-variable Calculus with emphases on conceptual understanding and applications. The course is ideal for students beginning in the engineering, physical, and social sciences. Distinguishing features of the course include: 1) the introduction and use of Taylor series and approximations from the beginning; 2) a novel synthesis of discrete and continuous forms of Calculus; 3) an emphasis on the conceptual over the computational; and 4) a clear, dynamic, unified approach.

Sep 28th 2026
5-12 Weeks
Advanced Linear Models for Data Science 2: Statistical Linear Models (Coursera) Coursera
Johns Hopkins University

Advanced Linear Models for Data Science 2: Statistical Linear Models (Coursera)

Welcome to the Advanced Linear Models for Data Science Class 2: Statistical Linear Models. This class is an introduction to least squares from a linear algebraic and mathematical perspective. Before beginning the class make sure that you have the following: a basic understanding of linear algebra and multivariate calculus; a basic understanding of statistics and regression models; at least a little familiarity with proof based mathematics; basic knowledge of the R programming language.

Sep 28th 2026
4 Weeks
Fibonacci Numbers and the Golden Ratio (Coursera) Coursera
The Hong Kong University of Science and Technology - HKUST

Fibonacci Numbers and the Golden Ratio (Coursera)

Learn the mathematics behind the Fibonacci numbers, the golden ratio, and how they are related. These topics are not usually taught in a typical math curriculum, yet contain many fascinating results that are still accessible to an advanced high school student. The course culminates in an explanation of why the Fibonacci numbers appear unexpectedly in nature, such as the number of spirals in the head of a sunflower.

Sep 28th 2026
3 Weeks
Differential Equations Part II Series Solutions (Coursera) Coursera
Korea Advanced Institute of Science and Technology - KAIST

Differential Equations Part II Series Solutions (Coursera)

This introductory courses on (Ordinary) Differential Equations are mainly for the people, who need differential equations mostly for the practical use in their own fields. So we try to provide basic terminologies, concepts, and methods of solving various types of differential equations as well as a rudimentary but indispensable knowledge of the underlying theory and some related applications.

Sep 28th 2026
5-12 Weeks
Calculus: Single Variable Part 3 - Integration (Coursera) Coursera
University of Pennsylvania

Calculus: Single Variable Part 3 - Integration (Coursera)

Calculus is one of the grandest achievements of human thought, explaining everything from planetary orbits to the optimal size of a city to the periodicity of a heartbeat. This brisk course covers the core ideas of single-variable Calculus with emphases on conceptual understanding and applications. The course is ideal for students beginning in the engineering, physical, and social sciences.

Sep 28th 2026
4 Weeks
Introduction to Logic (Coursera) Coursera
Stanford University

Introduction to Logic (Coursera)

This course is an introduction to Logic from a computational perspective. It shows how to encode information in the form of logical sentences; it shows how to reason with information in this form; and it provides an overview of logic technology and its applications - in mathematics, science, engineering, business, law, and so forth.

Sep 24th 2026
5-12 Weeks