“I wouldn’t be where I was without Dataquest. Be confident in what you learn with Dataquest. If you take the time to learn, you will be one of the few people in the world that can do what you do.”

Vicknesh Mano

Data Science Manager @Accenture

Course overview

Linear Algebra is a key branch of mathematics that is concerned with vectors, matrices, planes, and lines, and it helps to build blocks of machine learning algorithms.

In this course, you’ll learn how to define linear systems using linear algebra, how to represent a problem as a linear system, and how to solve linear systems by elimination.

You’ll learn how to define vectors using geometry, as well as how to perform vector operations and identify the link between linear combinations and solutions to linear systems. You’ll also learn how to perform matrix operations in NumPy, how to define the matrix inverse and transpose, and how to solve the matrix inverse in higher dimensions.

Finally, you’ll learn to identify the different solution sets to linear systems and define homogeneous and nonhomogeneous systems.

Best of all, you’ll learn by doing — you’ll practice and get feedback directly in the browser.

Key skills

  • Defining linear systems using linear algebra
  • Employing intermediate machine learning techniques

Course outline

Linear Algebra For Machine Learning [4 lessons]

Linear Systems 1h

Lesson Objectives
  • Represent a problem as a linear system
  • Solve linear systems by elimination

Vectors 1h

Lesson Objectives
  • Define vectors using geometry
  • Perform vector operations
  • Identify the link between linear combinations and solutions to linear systems

Matrix Algebra 1h

Lesson Objectives
  • Perform matrix operations in NumPy
  • Define the matrix inverse and transpose
  • Solve the matrix inverse in higher dimensions

Solution Sets 1h

Lesson Objectives
  • Identify the different solution sets to linear systems
  • Define homogenous and nonhomogenous systems

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Aaron Melton

Business Analyst at Aditi Consulting

“Dataquest starts at the most basic level, so a beginner can understand the concepts. I tried learning to code before, using Codecademy and Coursera. I struggled because I had no background in coding, and I was spending a lot of time Googling. Dataquest helped me actually learn.”


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Machine Learning Engineer at Twitter

“I liked the interactive environment on Dataquest. The material was clear and well organized. I spent more time practicing then watching videos and it made me want to keep learning.”


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Associate Data Scientist at Callisto Media

“I really love learning on Dataquest. I looked into a couple of other options and I found that they were much too handhold-y and fill in the blank relative to Dataquest’s method. The projects on Dataquest were key to getting my job. I doubled my income!”

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