Mastering Linear Algebra edX - online learning platform

Overview

This program will enable you to review the relevant topics and offer you an overview of the linear algebra common in most engineering bachelor programs. Learn more at this Mastering Linear Algebra Professional Certificate in collaboration with Delft University of Technology (TU Delft) - DelftX.

Key Facts

The courses in this program provide enough depth to cover the linear algebra you need to succeed in your engineering master’s or professional work in areas such as computer graphics, systems and control, machine learning, quantum computing and more.In the first course you will review all the basic concepts and practice and refresh the skills related to vectors and linear equations. The course focuses on vectors (from both algebraic and geometric perspectives) and solving linear equations.The second course will review all the basic concepts and practice and refresh the skills related to matrices and linear transformations. Topics covered include matrix algebra, determinants, eigenvalues and eigenvectors, diagonalization and singular value decomposition.

These courses are self-paced, self-contained and modular, to make it easier to review specific topics and practice as often as you want without having to follow the entire courses.

This program will refresh your knowledge, test your skills and review the relations between the various concepts in linear algebra. As review courses, you are expected to have previously studied or be familiar with most of the material.

This program is part of our series ‘Mastering Mathematics for Engineers’, together with ‘Mastering Calculus’ and ‘Mastering Probability and Statistics’.

Job Outlook

• In many engineering master’s programs or professions, you need to be familiar with linear algebra.
• A strong foundation in mathematics is critical for any aspiring or practicing engineer.
• Knowledge of linear algebra is needed to succeed in an engineering master’s or profession in areas such as computer graphics, systems and control, machine learning, quantum computing and more.