Calculus 1 (UNINETUNO)

EdX

Weston High School

On-Ramp to AP* Physics C: Mechanics (edX)

Sci: Physics

This course will help the students who have taken intro-level high-school physics to get ready for more advanced courses including AP Physics C: Mechanics. This short course is intended for the high-school students who have taken an introductory-level physics course, acquired some background in Mechanics and intend to take a more advanced course – for instance, AP Physics C.

Self Paced

Self-Paced

Algebra Trigonometry Physics

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UNINETTUNO OpenupEd

International Telematic University UNINETTUNO

Linear Algebra (UNINETTUNO)

Sci: Mathematics

Vector spaces, matrices and linear applications.

Self Paced Course - Start anytime

Self-Paced

Math Algebra Linear Algebra

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Coursera

Johns Hopkins University

Calculus through Data & Modeling: Precalculus Review (Coursera)

Sci: Mathematics

This course is an applications-oriented, investigative approach to the study of the mathematical topics needed for further coursework in single and multivariable calculus. The unifying theme is the study of functions, including polynomial, rational, exponential, logarithmic, and trigonometric functions. An emphasis is placed on using these functions to model and analyze data. Graphing calculators and/or the computer will be used as an integral part of the course.

Sep 7th 2026

4 Weeks

Calculus Trigonometry Logarithmic Functions

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EdX

University of Texas at Austin,UTAustinX

Linear Algebra - Foundations to Frontiers (edX)

CS: Software Engineering Sci: Mathematics

Learn the mathematics behind linear algebra and link it to matrix software development. Linear Algebra: Foundations to Frontiers (LAFF) is packed full of challenging, rewarding material that is essential for mathematicians, engineers, scientists, and anyone working with large datasets.

Self Paced

Self-Paced

Math Algebra Linear Algebra

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Coursera

Princeton University

Analytic Combinatorics (Coursera)

CS: Theory Sci: Mathematics

Analytic Combinatorics teaches a calculus that enables precise quantitative predictions of large combinatorial structures. This course introduces the symbolic method to derive functional relations among ordinary, exponential, and multivariate generating functions, and methods in complex analysis for deriving accurate asymptotics from the GF equations. All the features of this course are available for free. It does not offer a certificate upon completion.

Sep 7th 2026

5-12 Weeks

Math Calculus Analytic Combinatorics

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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.

Sep 7th 2026

4 Weeks

Statistics Analysis Machine Learning

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Coursera

Johns Hopkins University

Calculus through Data & Modeling: Differentiation Rules (Coursera)

Sci: Mathematics

Calculus through Data & Modeling: Differentiation Rules continues the study of differentiable calculus by developing new rules for finding derivatives without having to use the limit definition directly. These differentiation rules will enable the calculation of rates of change with relative ease the derivatives of polynomials, rational functions, algebraic functions, exponential and logarithmic functions, and trigonometric and inverse trigonometric functions.

Sep 7th 2026

5-12 Weeks

Math Calculus Modeling

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Coursera

CertNexus

Build Regression, Classification, and Clustering Models (Coursera)

Data Science

In most cases, the ultimate goal of a machine learning project is to produce a model. Models make decisions, predictions—anything that can help the business understand itself, its customers, and its environment better than a human could. Models are constructed using algorithms, and in the world of machine learning, there are many different algorithms to choose from. You need to know how to select the best algorithm for a given job, and how to use that algorithm to produce a working model that provides value to the business. This third course within the Certified Artificial Intelligence Practitioner (CAIP) professional certificate introduces you to some of the major machine learning algorithms that are used to solve the two most common supervised problems: regression and classification, and one of the most common unsupervised problems: clustering.

Sep 7th 2026

5-12 Weeks

ML Machine Learning Linear Algebra

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Coursera

Johns Hopkins University

Calculus through Data & Modeling: Limits & Derivatives (Coursera)

Sci: Mathematics

This first course on concepts of single variable calculus will introduce the notions of limits of a function to define the derivative of a function. In mathematics, the derivative measures the sensitivity to change of the function. For example, the derivative of the position of a moving object with respect to time is the object's velocity: this measures how quickly the position of the object changes when time advances. This fundamental notion will be applied through the modelling and analysis of data.

Sep 7th 2026

5-12 Weeks

Math Calculus Mathematics

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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.

Sep 7th 2026

5-12 Weeks

Math Calculus Mathematics

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Coursera

École Polytechnique Fédérale de Lausanne

Interest Rate Models (Coursera)

Economics & Finance

This course gives you an easy introduction to interest rates and related contracts. These include the LIBOR, bonds, forward rate agreements, swaps, interest rate futures, caps, floors, and swaptions. We will learn how to apply the basic tools duration and convexity for managing the interest rate risk of a bond portfolio. We will gain practice in estimating the term structure from market data. We will learn the basic facts from stochastic calculus that will enable you to engineer a large variety of stochastic interest rate models. In this context, we will also review the arbitrage pricing theorem that provides the foundation for pricing financial derivatives.

Sep 21st 2026

5-12 Weeks

Finance Business Calculus

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Coursera

Johns Hopkins University

Advanced Linear Models for Data Science 1: Least Squares (Coursera)

Statistics & Data Analysis Data Science

Welcome to the Advanced Linear Models for Data Science Class 1: Least Squares. 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 21st 2026

5-12 Weeks

Linear Algebra Linear Regression Data Science

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