Free Online Math Classes
478 courses

This course explores the general theory of zerosum, twoperson games.

Games without Chance: Combinatorial Game Theory
Spring 2013In this class, students can expand their insight into the structure of twoperson games through an understanding of mathematical theory.

In this class, students will discuss teaching methods in combinatorial geometry and receive an introduction to discrete and computational geometry.

This course from MIT explores geometric folding, including linkages, origami, and polyhedra.

This course studies primarily in twodimensional space but includes some study of threedimensional as well.

This geometry course reviews the language and notation of basic geometry, line segments, rays, angle measurement, and congruence.

This class geared toward high school and secondary students focuses on building the learner's conceptual knowledge of key geometrical areas, like points, lines, angles, triangles, quadrilaterals, and circles.

Geometry and Quantum Field Theory
Pavel Etingof, Math — Massachusetts Institute of Technology (MIT)
Fall 2002Geared toward math majors, this course provides an intensive introduction to perturbative quantum field theory, through functional integrals language.

This is a course designed for use as a complimentary resource or study guide for students who want to enhance their understanding to introductory geometry concepts.

This graduate level course discusses the geometry of manifolds and dives into topics like Lie groups, differentiable manifolds, and vector fields.

Students in this course will identify, measure, and calculate angles.

In this course, students will continue their studies of Euclid by learning about angles and their relation to each other.

This course discusses the geometrical aspects of circles, such as the parts, area, language, notation, and more.

Students will learn the foundational idea of congruent triangles in geometry.

These tutorials cover perimeter area and volume with and without algebra.

This course introduces the basic tools underpinning the journey to understanding Euclidean geometry, including the ideas of points, line segments, lines, rays, and planes.

In this course, students will gain a broader understanding of quadrilaterals beyond just squares and rectangles.

This course covers the fundamentals of right triangles and how they form the basis of some important conc3epts in analytic geometry.

In this tutorial, students will gain an understanding of a concept about triangles that is similar but not identical to congruency.

Students taking this course will learn about the special properties and parts of triangles.

In this course, students will identify different types of triangles, use similarity and congruence, and apply and prove triangle postulates.

80 problems from the released questions from the California Standards Test for Geometry are solved in this video series.

Graph Partitioning and Expanders
Spring 2013This course is researchoriented and intended for graduates, covering algorithms for graph partitioning and clustering, constructions of expander graphs, and more.

Learn fundamental calculator operations for the TI83.

This course has tips for making the basics of GCSE maths easier.

Saylor's purpose for this course was to give students a comprehensive understanding of the history of economic thinking and ideas.

This course provides a review of free, projective, and injective modules, direct limits, homology, and homology and derived functors in Algebra.

Honors Differential Equations
Vera Mikyoung Hur, Math — Massachusetts Institute of Technology (MIT)
Spring 2009This course is an extension of differential equations studies, with added emphasis on mathematical theory.

This module why proofs can help to determine if a result is true and how to start and use them.

This course is designed to review material that may be covered on the IB Mathematics SL exam.

This course observes prominent topics and theories in the subject of industrial organization.

Infinite Random Matrix Theory
Fall 2004In this class, students will learn about theories and methods behind the characterization of infinite random matrices.

This course provides a discussion on infinity, including uncountable infinity and denumerable infinity.

Integral Equations
Dionisios Margetis, Math — Massachusetts Institute of Technology (MIT)
Spring 2006In this class, students explore theories and techniques and applied mathematics perspectives on solving integral equations.

Intermediate Algebra
Fall 2010This course is geared towards students who have limited backgrounds in algebra and covers fundamental operations, special products and factors, functions and fractional equations, exponents, radicals, and quadratic equations.

In this course, students will build and apply what was learned in the introductory course in macroeconomics.

Saylor designed this course to expand students' knowledge of basic microeconomics.

Students will be provided with the necessary analytical framework for the study of international trade, which covers a vast array of topics related to the subject.

This is a great course for getting started on aerospace engineering.

Introduction to Analysis
Arthur Mattuck, Math — Massachusetts Institute of Technology (MIT)
Fall 2012This course provides a gentle, nontraditional introduction to the various elements of mathematical analysis.

Introduction to Analysis I covers metric spaces, convergence of sequences and series, continuity, differentiability, Riemann integral, sequences and series of functions, uniformity, and interchange of limit operations.

Category theory is a branch of mathematics that was formed to understand how different areas of the discipline relate to one another.

This course offers lectures and information on Computational Fluid Dynamics and more.

This is a short session that introduces compact linear operators on Banach spaces.

Covers systems of linear equations, first order differential equations, homogeneous differential equations, and nonhomogeneous differential equations and systems.

Topics covered in this course include algorithms, flow charts, and more.

Introduction to Functional Analysis
Richard Melrose, Math — Massachusetts Institute of Technology (MIT)
Spring 2009This course covers various functions and operators in functional mathematical analysis.

The introduction to graph theory and applications course offers instruction in the theorems related to graphs, such as the HavelHakimi theorem. It also considers walks, paths, circuits, cycles, distances, and adjacency matrices.

Introduction to Group Representations
Summer 2012This course examines the intersection of group representations and linear algebra. It also looks at number theory, analysis, algebraic geometry, chemistry, and the basic representation theory of finite groups.

Introduction to Lie Groups
Sigurdur Helgason, Math — Massachusetts Institute of Technology (MIT)
Fall 2004Drawing from the text Differential Geometry, Lie Groups and Symmetric Spaces by Sigurdur Helgason, this class focuses on the theory of Lie groups and its connection to differential geometry.

Primarily, this course's function is to bridge the gap between introductory mathematics in algebra and calculus with more advanced mathematical courses, such as analysis and abstract algebra.

Introduction to Mathematical Thinking
Fall 2012How do mathematicians think? Find out how, and how you can think like them, in this course.

Introduction To MATLAB Programming
Yossi Farjoun, Math — Massachusetts Institute of Technology (MIT)
Fall 2011This course examines the basics of general and MATLAB

Topics covered in this course include basics of nuclear power generation, nuclear theory, and more.

Introduction to Numerical Analysis
Laurent Demanet, Math — Massachusetts Institute of Technology (MIT)
Spring 2012The curriculum in this course is centered on basic techniques for efficiency in numerical science and engineering problems and solutions.

Introduction to Numerical Methods
Steven G. Johnson, Math — Massachusetts Institute of Technology (MIT)
Fall 2010This course covers advanced introductory topics in numerical linear algebra.

This course provides a glimpse into the complex world of partial differential equations.

Introduction to Partial Differential Equations
Jared Speck, Math — Massachusetts Institute of Technology (MIT)
Fall 2011This course explores diffusion, elliptic, and hyperbolic as the three main types of partial differential equations.

Introduction to Probability and Statistics
Dmitry Panchenko, Math — Massachusetts Institute of Technology (MIT)
Spring 2005This course provides a basic introduction to practical probability and statistics.

Introduction to Probability and Statistics
Deborah Nolan, Math — University of California, Berkeley (UC Berkeley)
Fall 2011This course, bestsuited for students who have a background in mathematics, covers relative frequencies, random variables, discrete probability, and estimation.

Students interested in probability theory, Saylor provides this introductory course.

Introduction to Probability Theory
K. Suresh Kumar, Math — Indian Institute of Technology Bombay (IIT Bombay)
N/AThis course will cover probability space, random variables, distribution functions, and more.

Students in this course will explore probability models, longterm averages, random variables and much more.

Students in this introductory class will become familiar with topics like central limit theorem, variance and others, all related to random variable processes.

Introduction to Real Analysis
Spring 2011Students explore real numbers, introductory topological topics, limits, sequences of numbers, continuity, sequences of functions, and series.

Introduction to Representation Theory
Pavel Etingof, Math — Massachusetts Institute of Technology (MIT)
Fall 2010This course provides an introduction of representation theory to undergraduatelevel students.

Topics in this course include satellite systems, orbits, signals and more.

Supplemented with video lectures from the Khan Academy, this course gives students a comprehensive introduction to statistics.

Introduction to statistics explores how we can make decisions based on data.

Students in this class will be introduced to experimental method in psychology and to mathematical techniques necessary for experimental research.

Introduction to Statistics
Fletcher Ibser, Math — University of California, Berkeley (UC Berkeley)
Fall 2012Standard measures of location, spread, and association; normal approximation; population and variables; and binomial distribution are covered in this course.

Introduction to Statistics
Soring 2009Topics include describing and summarizing data both graphically and numerically, probability, various distributions, parametric estimation and tests of significance, and exploration of bivariate data.

Introduction to Statistics: Descriptive Statistics
Ani Adhikari, Math — University of California, Berkeley (UC Berkeley)
Spring 2013This is an introductory statistics course that focuses on descriptive statistics, which presents numerical information in a useful way.

Introduction to Topology
James Munkres, Math — Massachusetts Institute of Technology (MIT)
Fall 2004This course explores various introductory topics in topology, including fundamental to modern analysis and geometry.

Jodie Broussard provides an introduction to trigonometry in this course from Florida State College at Jacksonville.

Introductory Probability and Statistics for Business
Fletcher Ibser, Math — University of California, Berkeley (UC Berkeley)
Spring 2012This course features study in descriptive statistics, probability models, estimates, sample surveys, tests of significance, and more.

This course covers basic inventory control for managers.

This course educates students on building a good theory of the labor market, including empirical implications that can be tested with real world data.

In this set of videos, LeBron James asks questions about math and science related to basketball, working out, and a little bit of earth history.

Linear Algebra is taught over the course of four units through Saylor in an alltext format that gives students the materials necessary to become practiced in the subject.

Linear algebra introduces students to the basic concepts of matrices, transformations, vectors, and vector spaces.

In this course, students learn about matrix algebra, Gaussian elimination, determinants, linear and affine subspaces, and more.

Students in this class learn how to solve linear equations, how to simplify problems to have linear characteristics, and understand basis, span, and kernel. The course also examines matrices and vectors.

Students in this course will learn about matrix theory and linear algebra.

In this course students learn about matrix theory and linear algebra.

This course from Georgia State University covers the theory and applications of matrix algebra, vector spaces, and linear transformations.

Linear Algebra  Communications Intensive
Andrew BrookeTaylor, Anna Lachowska, Math — Massachusetts Institute of Technology (MIT)
Spring 2004Intended as a supplement to linear algebra, this course provides a communicationsbased intensive study in the subject.

Students taking this course will gain a deeper understanding of the principles of linear algebra.

This course explores creating and moving between various coordinate systems.

Students will gain an understanding of how a set of vectors can be mapped to another set as well as how matrices are used to define linear transformations.

This course introduces the concepts of vectors and spaces.

Linear and Discrete Optimization
Friedrich Eisenbrand, Math — Ecole Polytechnique Federale De Laussane
Spring 2013See how computational mathematics, and linear and discrete optimization in particular, have a wide range of applications in everyday life with this course.

Linear Partial Differential Equations
Matthew Hancock, Math — Massachusetts Institute of Technology (MIT)
Fall 2006This course covers classical partial differential equations of applied mathematics.

Linear Partial Differential Equations: Analysis and Numerics
Steven G. Johnson, Math — Massachusetts Institute of Technology (MIT)
Fall 2010This course explains the basic analytical and computational tools of linear partial differential equations for practical use.

Linear Programming and Extensions
Prabha Sharma, Math — Indian Institute of Technology Kanpur (IIT Kanpur)
N/AThis course will cover the simplex algorithm, the duality theory, the Ellipsoid algorithm, and more.

Learn how to graph linear equations.

Take this course to understand the reasons for studying mathematics, with practical applications of mathematical ideas.

Students in this course will gain a repertoire of skills and techniques to solve fundamental problems in microeconomics and macroeconomics.

Taught by Tim Chartier, this course identifies applications of finite math in several aspects of life.

Students in this course use modules to learn calculus.