Stepik

Linear Algebra: Problems and Methods (Stepik)

Offered by Steklov Mathematical Institute,

The goal of the course is to explain the fundamental ideas of linear algebra and how to use them to find easy solutions of hard problems.

The goal of this course is to help you to find and understand the building blocks of linear algebra. Moreover, it is important to develop personal vision and intuition about them. This cannot be achieved by solving 1000 similar typical exam problems.

In this course you will be provided with a sort of "minimal linear algebra kit", so that you can manage the saved time yourself. In particular, you are encouraged to discuss the lessons here at stepic, to participate in competitions and other events at your campus, and to surf web resources such as math.stackexchange.com, mathoverflow.net, arxiv.org and of course Wikipedia. If you are enrolled in a traditional course of linear algebra, you will benefit from this course too, since it is not designed to substitute the traditional courses.

Go to Class

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

Related Courses

Coursera

Georgia Institute of Technology

Fundamentals of Engineering Exam Review (Coursera)

Engineering Sci: Physics

The purpose of this course is to review the material covered in the Fundamentals of Engineering (FE) exam to enable the student to pass it. It will be presented in modules corresponding to the FE topics, particularly those in Civil and Mechanical Engineering. Each module will review main concepts, illustrate them with examples, and provide extensive practice problems.

Nov 2nd 2026

5-12 Weeks

Math Statistics Probability

Coursera

University of Michigan

The Finite Element Method for Problems in Physics (Coursera)

Engineering Sci: Mathematics

This course is an introduction to the finite element method as applicable to a range of problems in physics and engineering sciences. The treatment is mathematical, but only for the purpose of clarifying the formulation. The emphasis is on coding up the formulations in a modern, open-source environment that can be expanded to other applications, subsequently.

Nov 2nd 2026

13-24 Weeks

Math Physics Linear Algebra

Coursera

University of Houston System

Math behind Moneyball (Coursera)

Statistics & Data Analysis Data Science

Learn how probability, math, and statistics can be used to help baseball, football and basketball teams improve, player and lineup selection as well as in game strategy.

Nov 9th 2026

5-12 Weeks

Math Business Statistics

Coursera

Stanford University

Machine Learning (Coursera)

Statistics & Data Analysis Data Science

Machine learning is the science of getting computers to act without being explicitly programmed. In the past decade, machine learning has given us self-driving cars, practical speech recognition, effective web search, and a vastly improved understanding of the human genome. Machine learning is so pervasive today that you probably use it dozens of times a day without knowing it. Many researchers also think it is the best way to make progress towards human-level AI. In this class, you will learn about the most effective machine learning techniques, and gain practice implementing them and getting them to work for yourself. More importantly, you'll learn about not only the theoretical underpinnings of learning, but also gain the practical know-how needed to quickly and powerfully apply these techniques to new problems.

Nov 2nd 2026

5-12 Weeks

Artificial Intelligence MATLAB Algorithms

Coursera

Johns Hopkins University

Precalculus: Mathematical Modeling (Coursera)

Sci: Mathematics

This course helps to build the foundational material to use mathematics as a tool to model, understand, and interpret the world around us. This is done through studying functions, their properties, and applications to data analysis. Concepts of precalculus provide the set of tools for the beginning student to begin their scientific career, preparing them for future science and calculus courses. This course is designed for all students, not just those interested in further mathematics courses.

Nov 2nd 2026

4 Weeks

Calculus Computer Science Modeling

Coursera

The Hong Kong University of Science and Technology - HKUST

Vector Calculus for Engineers (Coursera)

Sci: Mathematics

Vector Calculus for Engineers covers both basic theory and applications. In the first week we learn about scalar and vector fields, in the second week about differentiating fields, in the third week about multidimensional integration and curvilinear coordinate systems. The fourth week covers line and surface integrals, and the fifth week covers the fundamental theorems of vector calculus, including the gradient theorem, the divergence theorem and Stokes’ theorem. These theorems are needed in core engineering subjects such as Electromagnetism and Fluid Mechanics.

Nov 2nd 2026

5-12 Weeks

Math Calculus Mathematics

Coursera

Johns Hopkins University

Calculus through Data & Modeling: Applying Differentiation (Coursera)

Sci: Mathematics

As rates of change, derivatives give us information about the shape of a graph. In this course, we will apply the derivative to find linear approximations for single-variable and multi-variable functions. This gives us a straightforward way to estimate functions that may be complicated or difficult to evaluate. We will also use the derivative to locate the maximum and minimum values of a function. These optimization techniques are important for all fields, including the natural sciences and data analysis. The topics in this course lend themselves to many real-world applications, such as machine learning, minimizing costs or maximizing profits.

Nov 2nd 2026

5-12 Weeks

Math Calculus Data Modeling

Coursera

Imperial College London

Mathematics for Machine Learning: PCA (Coursera)

Data Science

This intermediate-level course introduces the mathematical foundations to derive Principal Component Analysis (PCA), a fundamental dimensionality reduction technique. We'll cover some basic statistics of data sets, such as mean values and variances, we'll compute distances and angles between vectors using inner products and derive orthogonal projections of data onto lower-dimensional subspaces. Using all these tools, we'll then derive PCA as a method that minimizes the average squared reconstruction error between data points and their reconstruction.

Nov 2nd 2026

4 Weeks

Statistics Analysis Machine Learning

Coursera

Duke University

Data Science Math Skills (Coursera)

Sci: Mathematics Data Science

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.

Nov 2nd 2026

4 Weeks

Math Algebra Probability

Coursera

University of Pennsylvania

English for Science, Technology, Engineering, and Mathematics (Coursera)

Languages & Literature

Welcome to English for Science, Technology, Engineering, and Mathematics, a course created by the University of Pennsylvania, and funded by the U.S. Department of State Bureau of Educational and Cultural Affairs, Office of English Language Programs. This course is designed for non-native English speakers who are interested in improving their English skills in the sciences. In this course, you will explore some of the most innovative areas of scientific study, while expanding your vocabulary and the language skills needed to share scientific information within your community.

Nov 2nd 2026

5-12 Weeks

English Technology Engineering

Coursera

Wesleyan University

Introduction to Complex Analysis (Coursera)

Sci: Mathematics

This course provides an introduction to complex analysis which is the theory of complex functions of a complex variable. We will start by introducing the complex plane, along with the algebra and geometry of complex numbers, and then we will make our way via differentiation, integration, complex dynamics, power series representation and Laurent series into territories at the edge of what is known today.

Nov 9th 2026

5-12 Weeks

Algebra Geometry Compilers

Coursera

Johns Hopkins University

Precalculus: Periodic Functions (Coursera)

Sci: Mathematics

Nov 2nd 2026

5-12 Weeks

Math Trigonometry Data Analysis