Are you interested in Data Science but lack the math background for it? Has math always been a tough subject that you tend to avoid? This course will teach you the most fundamental Linear Algebra that you will need for a career in Data Science without a ton of unnecessary proofs and concepts that you may never use. Consider this an expressway to Data Science with approachable methods and friendly concepts that will guide you to truly understanding the most important ideas in Linear Algebra.
Essential Linear Algebra for Data Science
Essential Linear Algebra for Data Science
This course is part of Expressway to Data Science: Essential Math Specialization
Instructor: James Bird
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4.4
(169 reviews)
Intermediate level
Recommended experience
Flexible schedule
Approx. 7 hours
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Prepare for a degree
What you'll learn
Solve real-world problems using the foundational concept of matrices and explain where those problems might arise.
Recognize what a matrix represents in n-dimensional space and how transformations act in that space
Identify key properties of any system of equations, such as independence, basis, rank, and more, and what they mean for the overall system.
Demonstrate your understanding of projections in lower dimensions, while being able to carry out higher dimension projections for real-world problems
Skills you'll gain
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Assessments
13 assignments
Taught in English
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This course is part of the Expressway to Data Science: Essential Math Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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There are 5 modules in this course
In this module we will learn what a matrix is and what it represents. We will explore how a system of linear equations can be expressed in a neat package via matrices. Lastly, we will delve into coordinate systems and provide visualizations to help you understand matrices in a more well-rounded way.
What's included
13 videos2 assignments
In this module we will learn how to solve a linear system of equations with matrix algebra.
What's included
6 videos2 assignments
In this module we will explore concepts and properties of linear systems. This includes independence, basis, rank, row space, column space, and much more.
What's included
15 videos3 assignments
In this module we will discuss projections and how they work. We will build on a foundation using 2-dimensional projections and explore the concept in higher dimensions over time.
What's included
8 videos3 assignments
In this module we will learn how to compute the determinant of a matrix. Afterwards, Eigenvalues and Eigenvectors will be covered.
What's included
9 videos3 assignments
Instructor
Instructor ratings
4.7 (65 ratings)Offered by
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Taking this course by University of Colorado Boulder may provide you with a preview of the topics, materials and instructors in a related degree program which can help you decide if the topic or university is right for you.
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4.4
169 reviews
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Showing 3 of 169
LH
5
Reviewed on May 9, 2022
Well-explained and comprehensive. I thought it was going to be a rough course but Professor Bird is very thorough and concise in his lectures.
TM
5
Reviewed on May 14, 2023
Good course overall. Instructor explained the concepts really well.
RJ
5
Reviewed on May 22, 2023
Great professor. Easy to follow and exercises are good enough.
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