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Numerical Methods for Engineers (Coursera)

Numerical Methods for Engineers covers the most important numerical methods that an engineer should know. We derive basic algorithms in root finding, matrix algebra, integration and interpolation, ordinary and partial differential equations. We learn how to use MATLAB to solve numerical problems. Access to MATLAB [...]

Matrix Factorization and Advanced Techniques (Coursera)

In this course you will learn a variety of matrix factorization and hybrid machine learning techniques for recommender systems. Starting with basic matrix factorization, you will understand both the intuition and the practical details of building recommender systems based on reducing the dimensionality of the user-product preference space. [...]

Basic Recommender Systems (Coursera)

This course introduces you to the leading approaches in recommender systems. The techniques described touch both collaborative and content-based approaches and include the most important algorithms used to provide recommendations. You'll learn how they work, how to use and how to evaluate them, pointing out benefits and limits of [...]

Matrix Algebra for Engineers (Coursera)

This course is all about matrices, and concisely covers the linear algebra that an engineer should know. The mathematics in this course is presented at the level of an advanced high school student, but typically students should take this course after completing a university-level single variable calculus [...]

Matrix Methods (Coursera)

Mathematical Matrix Methods lie at the root of most methods of machine learning and data analysis of tabular data. Learn the basics of Matrix Methods, including matrix-matrix multiplication, solving linear equations, orthogonality, and best least squares approximation. Discover the Singular Value Decomposition that plays a fundamental [...]

Divide and Conquer, Sorting and Searching, and Randomized Algorithms (Coursera)

The primary topics in this part of the specialization are: asymptotic ("Big-oh") notation, sorting and searching, divide and conquer (master method, integer and matrix multiplication, closest pair), and randomized algorithms (QuickSort, contraction algorithm for min cuts).

Bases Matemáticas: Algebra (edX)

En este curso se tratan los sistemas de ecuaciones, las matrices y cómo usarlas para resolverlos. En este curso se recordará lo que es una ecuación con una única incógnita y cómo solucionarla.

Linear Algebra II: Matrix Algebra (edX)

This course takes you through roughly three weeks of MATH 1554, Linear Algebra, as taught in the School of Mathematics at The Georgia Institute of Technology. Your ability to apply the concepts that we introduced in our previous course is enhanced when you can perform algebraic operations with matrices. [...]

Linear Algebra I: Linear Equations (edX)

This course takes you through the first three weeks of MATH 1554, Linear Algebra, as taught in the School of Mathematics at The Georgia Institute of Technology. Systems of equations live at the heart of linear algebra. In this course you will explore fundamental concepts by exploring definitions and [...]

Create a Value versus Complexity Matrix in Google Sheets (Coursera)

Self Paced
Create a Value versus Complexity Matrix in Google Sheets (Coursera)
Free Course
Categories
Effort
Languages
In this 2-hour long project-based course, you will create a Value versus Complexity Matrix in Google Sheets and learn how to interpret the outcomes to prioritize product features. In the process, you will review the basics of this prioritization framework as well as Google Sheets functionality such as lookup [...]