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# Mathematics Textbooks and Full Courses

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This online course is designed to help anyone teach – and learn – with a 21st century approach to knowledge and teaching. Lesson 1 of the course shares important evidence we now have about the working of the brain, that is meaningful for all subjects and ages – and lives. We then move to thinking together about the data filled world in which we live, to prepare students for their future in a world of data.
The aim of a data science approach is not to add new standards or content to your teaching, it is about interacting with your content in a data science way – that is fun, interesting and creative. In the course you will experience lessons that you can take and use with your students, and you will see lots of classroom and lesson examples. Whether you are a kindergarten teacher, a high school history or maths teacher, an administrator or parent, or someone just curious about data science, there will be ideas for you.

Subject:
Mathematics
Statistics and Probability
Material Type:
Full Course
Teaching/Learning Strategy
Author:
YouCubed
03/04/2021
Conditional Remix & Share Permitted
CC BY-NC-SA
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Learn the fundamentals of machine learning to help you correctly apply various classification and regression machine learning algorithms to real-life problems.

Subject:
Applied Science
Computing and Information
Engineering
Mathematics
Statistics and Probability
Material Type:
Full Course
Provider:
Delft University of Technology
Provider Set:
TU Delft OpenCourseWare
Author:
Hanne Kekkonen
Tom Viering
07/28/2023
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CC BY-NC-SA
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A continuation of MATH 2253. Topics include differentiation and integration of transcendental functions,
integration techniques, indeterminate forms, infinite sequences and series, Taylor and Maclaurin series,
parametric equations, L'Hopital's Rule, improper integrals, and polar coordinates.

Subject:
Calculus
Mathematics
Material Type:
Full Course
Provider:
Kennesaw State University
Author:
Lake Ritter
10/03/2022
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CC BY-NC-SA
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Advanced Analytic Methods in Science and Engineering is a comprehensive treatment of the advanced methods of applied mathematics. It was designed to strengthen the mathematical abilities of graduate students and train them to think on their own.

Subject:
Mathematics
Material Type:
Full Course
Provider:
MIT
Provider Set:
MIT OpenCourseWare
Author:
Cheng, Hung
09/01/2004
Conditional Remix & Share Permitted
CC BY-NC-SA
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This course analyzes the functions of a complex variable and the calculus of residues. It also covers subjects such as ordinary differential equations, partial differential equations, Bessel and Legendre functions, and the Sturm-Liouville theory.

Subject:
Calculus
Mathematics
Material Type:
Full Course
Provider:
MIT
Provider Set:
MIT OpenCourseWare
Author:
Bush, John
Margetis, Dionisios
09/01/2004
Conditional Remix & Share Permitted
CC BY-NC-SA
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This graduate-level course focuses on current research topics in computational complexity theory. Topics include: Nondeterministic, alternating, probabilistic, and parallel computation models; Boolean circuits; Complexity classes and complete sets; The polynomial-time hierarchy; Interactive proof systems; Relativization; Definitions of randomness; Pseudo-randomness and derandomizations;Interactive proof systems and probabilistically checkable proofs.

Subject:
Applied Science
Computer Science
Engineering
Mathematics
Material Type:
Full Course
Provider:
MIT
Provider Set:
MIT OpenCourseWare
Author:
Moshkovitz, Dana
02/01/2016
Conditional Remix & Share Permitted
CC BY-NC-SA
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The focus of the course is the concepts and techniques for solving the partial differential equations (PDE) that permeate various scientific disciplines. The emphasis is on nonlinear PDE. Applications include problems from fluid dynamics, electrical and mechanical engineering, materials science, quantum mechanics, etc.

Subject:
Mathematics
Material Type:
Full Course
Provider:
MIT
Provider Set:
MIT OpenCourseWare
Author:
Rosales, Rodolfo
09/01/2009
Conditional Remix & Share Permitted
CC BY-NC-SA
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0.0 stars

This class covers the analysis and modeling of stochastic processes. Topics include measure theoretic probability, martingales, filtration, and stopping theorems, elements of large deviations theory, Brownian motion and reflected Brownian motion, stochastic integration and Ito calculus and functional limit theorems. In addition, the class will go over some applications to finance theory, insurance, queueing and inventory models.

Subject:
Mathematics
Statistics and Probability
Material Type:
Full Course
Provider:
MIT
Provider Set:
MIT OpenCourseWare
Author:
Gamarnik, David
09/01/2013
Unrestricted Use
CC BY
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0.0 stars

This course discusses how to use algebra for a variety of everyday tasks, such as calculate change without specifying how much money is to be spent on a purchase, analyzing relationships by graphing, and describing real-world situations in business, accounting, and science.

Subject:
Algebra
Mathematics
Material Type:
Full Course
Provider:
The Saylor Foundation
08/28/2013
Unrestricted Use
CC BY
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0.0 stars

In this course students gain proficiency in Linear Equations, Linear Inequalities, Graphing linear equations, Solving Systems of Equations, Simplifying with Polynomials, Division of Polynomials, Factoring Polynomials, Developing a Factoring Strategy, and Solving Other Algebraic Equations.

Subject:
Career and Technical Education
Education
Mathematics
Material Type:
Full Course
01/29/2018
Unrestricted Use
CC BY
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0.0 stars

The College and Career Readiness Standards for Level E (High School) outline the outcomes for this course.In this course students gain proficiency in Functions, Linear Functions, Solving Quadratics, Quadratic Functions, Exponential Functions, and Logarithmic Functions.

Subject:
Career and Technical Education
Education
Mathematics
Material Type:
Full Course
01/29/2018
Conditional Remix & Share Permitted
CC BY-NC-SA
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This undergraduate level Algebra I course covers groups, vector spaces, linear transformations, symmetry groups, bilinear forms, and linear groups.

Subject:
Algebra
Mathematics
Material Type:
Full Course
Provider:
MIT
Provider Set:
MIT OpenCourseWare
Author:
Artin, Michael
09/01/2010
Conditional Remix & Share Permitted
CC BY-NC-SA
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This undergraduate level course follows Algebra I. Topics include group representations, rings, ideals, fields, polynomial rings, modules, factorization, integers in quadratic number fields, field extensions, and Galois theory.

Subject:
Algebra
Mathematics
Material Type:
Full Course
Provider:
MIT
Provider Set:
MIT OpenCourseWare
Author:
Artin, Michael
02/01/2011
Conditional Remix & Share Permitted
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Algebra II is the second semester of a year-long introduction to modern algebra. The course focuses on group representations, rings, ideals, fields, polynomial rings, modules, factorization, integers in quadratic number fields, field extensions, and Galois theory.
These notes, which were created by students in a recent on-campus 18.702 Algebra II class, are offered here to supplement the materials included in OCW’s version of 18.702. They have not been checked for accuracy by the instructors of that class or by other MIT faculty members.

Subject:
Algebra
Mathematics
Material Type:
Full Course
Provider:
MIT
Provider Set:
MIT OpenCourseWare
02/01/2022
Conditional Remix & Share Permitted
CC BY-NC-SA
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Algebra I is the first semester of a year-long introduction to modern algebra. Algebra is a fundamental subject, used in many advanced math courses and with applications in computer science, chemistry, etc. The focus of this class is studying groups, linear algebra, and geometry in different forms.
These notes, which were created by students in a recent on-campus 18.701 Algebra I class, are offered here to supplement the materials included in OCW’s version of 18.701. They have not been checked for accuracy by the instructors of that class or by other MIT faculty members.

Subject:
Algebra
Mathematics
Material Type:
Full Course
Provider:
MIT
Provider Set:
MIT OpenCourseWare
09/01/2021
Conditional Remix & Share Permitted
CC BY-NC-SA
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0.0 stars

This course covers the applications of algebra to combinatorics. Topics include enumeration methods, permutations, partitions, partially ordered sets and lattices, Young tableaux, graph theory, matrix tree theorem, electrical networks, convex polytopes, and more.

Subject:
Algebra
Mathematics
Material Type:
Full Course
Provider:
MIT
Provider Set:
MIT OpenCourseWare
Author:
Postnikov, Alexander
02/01/2019
Conditional Remix & Share Permitted
CC BY-NC-SA
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This course covers the fundamental notions and results about algebraic varieties over an algebraically closed field. It also analyzes the relations between complex algebraic varieties and complex analytic varieties.

Subject:
Algebra
Geometry
Mathematics
Material Type:
Full Course
Provider:
MIT
Provider Set:
MIT OpenCourseWare
Author:
Olsson, Martin