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129 Best + Free Math Courses & Certificates [2026]
Ranked by Michael Kuhlman, CourseDuck's founder, from student reviews across every provider. How we rank
Our top picks
- Become a Probability & Statistics Master [Udemy]
- Become an Algebra Master [Udemy]
- Become a Calculus 1 Master [Udemy]
- Master the Fundamentals of Math [Udemy]
- Python for linear algebra (for absolute beginners) [Udemy]
- Mathematical Foundations of Machine Learning [Udemy]
- Become a Linear Algebra Master [Udemy]
- Master linear algebra: theory and implementation in code [Udemy]
- Become a Trigonometry & Precalculus Master [Udemy]
- Workshop in Probability and Statistics [Udemy]
About the best Math courses
Frequently asked questions
The most-reviewed course in this category is Become a Probability & Statistics Master by Krista King, with about 14,800 reviews at 4.8 as of October 2026. Her Become an Algebra Master (about 13,500 reviews at 4.7) and Become a Calculus 1 Master (about 13,100) are close behind.
Algebra, calculus, linear algebra, probability, discrete math, trigonometry, geometry and differential equations, from grade-school arithmetic and mental math up to university level.
Paid Udemy video courses include a certificate of completion when you finish; free courses and practice-test-only courses do not. It shows you did the work, but it is not academic credit and will not replace a school or college math course on a transcript.
1
Become a Probability & Statistics Master (2026)
A math-class style intro to probability and statistics from Krista King, with 148 short lectures, 58 quizzes and 8 workbooks, rated 4.8 by nearly 15,000 students.
Best for: Students in a first probability and statistics class, or adults who want a slow, practice-heavy refresher without software.
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- Read-first, then-watch format: 79 text notes precede the videos and one student says it makes lectures click.
- 58 quizzes plus 8 bonus workbooks give a lot of practice for a stats course.
- Refreshed in April 2026, with 4.8 stars across nearly 15,000 reviews.
- Sampling and hypothesis testing get over five hours between them, the deepest parts of the syllabus.
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- Quiz answers come without worked explanations, so a wrong answer can be hard to trace.
- One reviewer reports slides that cut off early and quizzes on material not covered.
- Light on probability theory: one section of 74 minutes, most of the time goes to statistics.
2
Become an Algebra Master (2026)
A 16-hour Algebra 1 and 2 path with short videos, notes and a quiz on nearly every topic, built for self-studiers and refreshers who want practice, not proofs.
Best for: Adults refreshing school algebra, or students who want Algebra 1 and 2 in one place with lots of quiz practice.
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- Short videos paired with notes and a quiz for each topic, so every lesson has a built-in check
- Covers Algebra 1 and Algebra 2 in one place, from order of operations to logarithms
- Reviewers call the explanations clear and to the point, with a pace that holds attention
- Section workbooks add extra practice problems on top of the quizzes
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- Computational rather than rigorous, so proofs and deeper theory are not the focus
- One low-star reviewer says the Algebra 2 half feels like reading from a textbook
- One reviewer finds the pace a bit fast and wants a way to slow the audio down
3
Become a Calculus 1 Master (2026)
A 12.8-hour Calc 1 course on limits, derivatives and their applications, with 76 quizzes and 19 bonus workbooks of extra practice problems.
Best for: Students taking or about to take college Calc 1 who want short, step-by-step videos plus lots of quizzes.
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- Short step-by-step videos with text notes for each lesson, easy to skim or rewatch
- 76 quizzes plus 19 workbooks give plenty of practice across limits, derivatives and applications
- Covers the tricky topics students worry about, like the chain rule, related rates and optimization
- Updated April 2026 and used by about 99,000 students, with 9,052 five-star reviews
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- Quiz answers show no worked explanation, a repeat complaint in the three-star reviews
- One reviewer felt big jumps between the videos and the harder exercises and workbooks
- Lecture notes have some typos, and a reviewer wanted more practice and less definition reading
4
Master the Fundamentals of Math (2026)
Krista King's clear, plain-spoken refresher on arithmetic, from negative numbers to radicals, with 48 quizzes and workbooks for adults and middle schoolers.
Best for: Adults or middle schoolers rusty on fractions and exponents who want a calm restart before algebra.
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- Reviewers back after a decade away from math call the explanations clear and a smooth way to restart
- 48 quizzes and 9 workbooks across 11 sections let you check each topic before moving on
- A non-native English speaker says everything was simple to follow, and others replay lessons until they click
- Updated May 2026 and rated 4.7 across more than 12,000 reviews, with most giving five stars
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- Stops at scientific notation, so there is no algebra, geometry or calculus here
- A 2-star reviewer found the material easy, the videos short and the explanations hard to follow
- One reviewer says the built-in AI Assistant is useless for this content
5
Python for linear algebra (for absolute beginners) (2026)
A free, under-two-hour taster that teaches basic Python and the big ideas of vectors and matrices in a browser, so nothing needs installing.
Best for: Complete beginners who want a free, two-hour look at Python and linear algebra before committing to a longer course.
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- Runs in the browser, so no Python install is needed to get started
- Assignments push students to search things out, which one reviewer says builds confidence
- Cohen speaks slowly with a neutral accent, easy to follow even without subtitles
- Free and about two hours long, so trying it costs almost nothing
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- Skims each topic; reviewers want more depth in the math and in NumPy and pyplot methods
- No quizzes, no graded coding exercises and no certificate of completion
- Too short to build real skill, it works as a taster that points to longer courses
6
Mathematical Foundations of Machine Learning (2024)
A 16-hour tour of the linear algebra and calculus behind ML, coded in NumPy, TensorFlow and PyTorch, with the promised statistics and optimization content still missing.
Best for: Python users of scikit-learn or Keras who want the linear algebra and calculus behind the models, coded in three libraries.
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- Clear, easy explanations that reviewers say work even for people new to the maths
- Same ideas coded in NumPy, TensorFlow and PyTorch, so the demos transfer to real work
- Covers eigenvectors, SVD, PCA, gradients and the chain rule as ML actually uses them
- About 90% of the 8,573 ratings are four or five stars
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- Promised statistics and optimization content never appeared, only a short probability section
- Few visuals and few real-world ML examples, so some topics feel dry, one reviewer says
- Audio volume jumps around, and some links to the course code no longer work
7
Become a Linear Algebra Master (2026)
What You'll Learn
- Operations on one matrix, including solving linear systems, and Gauss-Jordan elimination
- Operations on two matrices, including matrix multiplication and elimination matrices
- Matrices as vectors, including linear combinations and span, linear independence, and subspaces
- Dot products and cross products, including the Cauchy-Schwarz and vector triangle inequalities
- Matrix-vector products, including the null and column spaces, and solving Ax=b
- Transformations, including linear transformations, projections, and composition of transformations
- Inverses, including invertible and singular matrices, and solving systems with inverse matrices
- Determinants, including upper and lower triangular matrices, and Cramer's rule
- Transposes, including their determinants, and the null (left null) and column (row) spaces of the transpose
- Orthogonality and change of basis, including orthogonal complements, projections onto a
8
Master linear algebra: theory and implementation in code (2026)
What You'll Learn
- Understand theoretical concepts in linear algebra, including proofs
- Implement linear algebra concepts in scientific programming languages (MATLAB, Python)
- Apply linear algebra concepts to real datasets
- Ace your linear algebra exam!
- Apply linear algebra on computers with confidence
- Gain additional insights into solving problems in linear algebra, including homeworks and applications
- Be confident in learning advanced linear algebra topics
- Understand some of the important maths underlying machine learning
- The math underlying most of AI (artificial intelligence)
9
Become a Trigonometry & Precalculus Master (2026)
What You'll Learn
- Angles and their measure, including degrees, DMS and radians
- Six circular functions, including sine, cosine, tangent, cosecant, secant, and cotangent
- The unit circle, including finding sine and cosine, and how to complete a triangle
- Angles in circles, including oriented arcs, circular sectors, and linear and angular velocity
- Graphing the trig functions, including sine and cosine graphs, and transformations
- Inverse trig functions, including their graphs
- Trig identities, including even-odd, sum-difference, half-angle, double-angle, product-to-sum, and sum-to-product identities
- The law of sines and the law of cosines, including Heron's formula
- Polar curves, including converting coordinates and graphing polar curves
- Complex numbers, including polar forms and De Moivre's theorem
- Matrices, including solving systems, Gauss-Jordan elimination, and transformations and inverses
- Partial frac
10
Workshop in Probability and Statistics (2020)
What You'll Learn
- By the end of this workshop you should be able to pass any introductory statistics course
- This workshop will teach you probability, sampling, regression, and decision analysis
11
Become a Calculus 2 Master (2026)
What You'll Learn
- Integrals, including approximating area, the dreaded Fundamental Theorem of Calculus, and every kind of integration technique
- Applications of Integrals, including volume of revolution with disks, washers and shells, and all kinds of real world applications
- Polar & Parametric, including how to sketch polar curves and find the area bounded by polar curves
- Sequences & Series, including all the convergence tests, and Taylor and Maclaurin series