Ementorhub

What you'll learn

Use Python to solve vector equations

Apply linear algebra concepts such as the inverse of a matrix, row reduction, and eigenvalues and eigenvectors

Use regression models

Apply linear algebra to analyze data, create, and make predictions based off of a regression model

Skills you'll gain

NumPy

Regression Analysis

Data Manipulation

Scikit Learn (Machine Learning Library)

Data Wrangling

Machine Learning Methods

Jupyter

Python Programming

Data Analysis

Linear Algebra

Predictive Modeling

Data Visualization Software

Specialization - 4 course series

In this course, we'll cover the fundamentals of linear algebra, including systems of linear equations, matrix operations, and vector equations. Whether you’ve learned some of these concepts before and are looking for a refresher or you’re brand new to the ideas we’ll cover, you’ll find the materials to support you. Let's get started!

In this course, you'll be introduced to finding inverses and matrix algebra using Python. You will also practice using row reduction to solve linear equations as well as practice how to define linear transformations. Let's get started!

In this course, you'll learn how to distinguish between the different types of regression models. You will apply the Method of Least Squares to a dataset by hand and using Python. In addition, you will learn how to employ a linear regression model to identify scenarios. Let's get started!

In this course, you'll review the specifics of the Capstone project. In addition, you will create and run your regression model and share your results with your peers. Let's get started!

Fundamental Linear Algebra Concepts with Python

Building Regression Models with Linear Algebra

Capstone: Data Science Problem in Linear Algebra Framework