Linear Algebra Courses and Certifications

Matrix Algebra for Engineers

767 reviews

This course is all about matrices, and concisely covers the linear algebra that an engineer should know. We define matrices and how to add and multiply them, and introduce some special types of matrices.

• Coursera
• 19 hours 31 minutes
• On-Demand
• Free Online Course (Audit)

• Best of All Time

Introduction to Linear Models and Matrix Algebra

12 reviews

Learn to use R programming to apply linear models to analyze data in life sciences.

• edX
• 4 weeks, 2-4 hours a week
• On-Demand
• Free Online Course (Audit)

Linear Algebra - Foundations to Frontiers

15 reviews

Learn the mathematics behind linear algebra and link it to matrix software development.

• edX
• 15 weeks, 6-10 hours a week
• On-Demand
• Free Online Course (Audit)

Differential Equations for Engineers

346 reviews

This course is about differential equations and covers material that all engineers should know. Both basic theory and applications are taught.

• Coursera
• 1 day 2 hours 48 minutes
• On-Demand
• Free Online Course (Audit)

Mathematics for Machine Learning: Linear Algebra

9 reviews

Explore linear algebra fundamentals and their applications in machine learning, covering vectors, matrices, eigenvalues, and practical implementations in Python for data-driven tasks.

• Coursera
• 18 hours 50 minutes
• On-Demand
• Free Online Course (Audit)

Linear Algebra

3 reviews

This course covers matrix theory and linear algebra, emphasizing topics useful in other disciplines such as physics, economics and social sciences, natural sciences, and engineering.

• MIT OpenCourseWare
• 36 hours
• On-Demand
• Free Video

Matrix Methods in Data Analysis, Signal Processing, and Machine Learning

3 reviews

This course reviews linear algebra with applications to probability and statistics and optimization–and above all a full explanation of deep learning.

• MIT OpenCourseWare
• 28 hours
• On-Demand
• Free Video

Learn linear algebra by doing: you will code your own library of linear algebra functions!

• Udacity
• 16 weeks
• On-Demand
• Free Online Course

Learn how to calculate eigenvalues and eigenvectors and why they are important for AI applications.

• Udacity
• 1 week
• On-Demand
• Free Online Course

Introduction to Linear Algebra for Machine Learning

Master essential linear algebra concepts and operations needed for machine learning, from vectors and matrices to determinants and linear dependency, with hands-on Python implementation.

• CodeSignal
• On-Demand
• Free Certificate

Linear Algebra: Linear Systems and Matrix Equations

104 ratings at Coursera

Explore linear systems, matrices, and vector equations, gaining foundational skills in linear algebra. Learn to solve and classify linear systems, understand linear transformations, and apply concepts to real-world problems.

• Coursera
• 10 hours 9 minutes
• On-Demand
• Free Online Course (Audit)

Linear Algebra: Matrix Algebra, Determinants, & Eigenvectors

48 ratings at Coursera

Develop matrix algebra techniques, study determinants, and explore eigenvectors to analyze linear transformations. Apply concepts to Markov chains and Google PageRank algorithm.

• Coursera
• 14 hours 53 minutes
• On-Demand
• Free Online Course (Audit)

Linear Algebra: Orthogonality and Diagonalization

30 ratings at Coursera

Explore orthogonality, diagonalization, and symmetric matrices, gaining skills applicable to AI and machine learning. Develop a strong foundation for advanced studies in data science and mathematics.

• Coursera
• 9 hours 15 minutes
• On-Demand
• Free Online Course (Audit)

Microcredential

Linear Algebra from Elementary to Advanced

Comprehensive introduction to linear algebra, covering vectors, matrices, and their applications. Emphasizes both algebraic and geometric understanding, preparing students for advanced topics in various fields.

• Coursera
• On-Demand
• Paid Course
• 3 courses

MIT - A 2020 Vision of Linear Algebra, Spring 2020

1 review

Professor Strang presents a fresh approach to linear algebra, focusing on matrices. This concise series covers key concepts like column space, orthogonality, eigenvalues, and solving linear systems.

• YouTube
• 1 hour 30 minutes
• On-Demand
• Free Video