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Learner Reviews & Feedback for Essential Linear Algebra for Data Science by University of Colorado Boulder

80 ratings

About the Course

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. This course is designed to prepare learners to successfully complete Statistical Modeling for Data Science Application, which is part of CU Boulder's Master of Science in Data Science (MS-DS) program. Logo courtesy of Dan-Cristian Pădureț on

Top reviews


Aug 11, 2022

It is a very informative course, and the coach made it simple and enjoyable.

Thank you, Dr. James, for your innovative explanation of the material.

Take this course and do not hesitate.


Aug 1, 2022

Perfect refresher course, gradually increasing in complexity and workload but James make the connections to previous content clear all the way. Highly recommended course!

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1 - 25 of 32 Reviews for Essential Linear Algebra for Data Science

By ralf p

Apr 24, 2022

Simple to follow. Easily explained. Good for revision as well as starting fresh

By Ross M

Sep 24, 2022

Before getting into the course evaluation: James seems like a well-intentioned instructor and good person who put a lot of work into this course. As a former teacher myself, I know it can be hard to not take criticism personally. So please know that none of what is below is personal.

The course is a series of linear algebra drills with no connection to data science concepts or applications. A data scientist needs to develop a conceptual foundation that helps them **use linear algebra to solve data analysis problems** using programming languages or statistical packages. This is a lofty learning outcome and a big shift away from traditional math education practice, so it would be understandable if a course were to aim for this and come up short.

This course, however, is simply drill and kill math with no clear objective. There was no connection to data science, no demonstration of practical appliations, no focus on higher-level conceptual understandings. Memorizing procedures that in practice are always carried out by computers is only valuable to the people who either will will write code to implement the procedures from scratch or will develop new mathematical procedures entirely. I'm guessing neither of these groups are not the target for this course.

An analogy: Imagine somebody offered a "Thermodynamics for HVAC Technicians" course and then spent weeks on hand calculations of energy transfer or entropy in the abstract. Being able to calculate energy transfer by hand isn't necessary for learning to fix an air conditioner, and being able to calculate eigenvectors by hand isn't necessary for learning to use PCA. The concepts are the point: What data science problem does an eigenvector solve? Why does the eigenvector solve it? How can one make sure they're using the eigenvector effectively in real-world context (in which the eigenvector has been calculated by a computer). As a practicing data scientist who never took a formal linear algebra course before, I can say that I do not know the answer to those questions any more so than before I took this course. That is my biggest disappointment.

A more effective course would start with a data analysis problem, then walk through conceptually what solving it requires, then introduce just enough linear algebra concepts to help the student develop that "under the hood" understanding that allows them to recognize when to apply the solution to other problems and how to do so effectively. Quizzes would then give them an opportunity to do just that.

Perhaps subsequent courses in the series revisit the procedures drilled here and eventually illustrate their application, but it's the application that should be the focus up front, with linear algebra concepts introduced as needed to solve the problems. Hand calculations would be used sparingly if at all just to build conceptual-level understandings. Courses would build up with progressively more challenging data science problems to solve, with each introducing the relevant linear algebra concepts just-in-time to solve the problem.

By Chris F

May 18, 2022

This is a very well explained course, put together nicely with bitesize lessons that consistently keep the dopamine flowing. An added bonus to this course is the topic area, in relation to the under-subscribed Tech industry, giving learners an added edge when attempting to enter the Data Science field.

By Leon H

May 10, 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.

By Sidra R

Apr 30, 2022

A very succint course. It's great for a beginner and can be easily understood. :) The quizzes are easy too.

By Calvin K L Y

Apr 28, 2022

Great introduction to Linear Algebra for beginners!

By Steve R

Mar 24, 2022

Very well done, conducted at just the right pace

By Bakang M

Jun 16, 2022

I love the way the course was conducted with fluency and the quizzes are no problem although not a sail through either for someone who has attempted multiple external questions.Finally, it is good for a beginner-intermediate individual or anyone looking to recap their L A concepts.

By 马镓浚

Oct 1, 2022

A quite succint course. Good for review or have some basic understanding of linear algebra. But if you want to have a thorough understanding of linear algebra, I think this course would not be enough and you should maybe use this course as a supplementary.

By John N

Jun 24, 2022

One of the best courses that I have found in Coursera. The material was challenging, but not overwhelming. Additionally, the istructor was phenomenal. My one recommendation would be to also go a little bit into how the computations are applicable to data science, rather than just go through the mechanics. Applications would likely be better in a follow on course, once the student is confident with the basic mechanics. Nevertheless, a truly phenomenal course and instructor.

By John K

Jul 8, 2022

I thought this was a really great course. The instructor explained things well and didn't assume that you know everything already (like some other courses). This wasn't even a required course for my MSDS program but I found it very useful for filling in some knowledge gaps and will help me as I continue my Master's in Data Science.


Jul 13, 2022

An awesome introductory level course to linear algebra. Very succinct, well-organized, and covers most of the important basics of linear algebra. Definitely recommend it to students who are completely new to linear algebra or students who have some previous knowledge about linear algebra but need a review.

By Heidi R

Oct 5, 2022

This course is easy to understand for a non-native speaker like me. I learned a lot from it and it encouraged me to build my confidence in mathematics. I am grateful to all the teachers of this course.

By Taleb A

Aug 12, 2022

It is a very informative course, and the coach made it simple and enjoyable.

Thank you, Dr. James, for your innovative explanation of the material.

Take this course and do not hesitate.

By Søren F

Aug 2, 2022

Perfect refresher course, gradually increasing in complexity and workload but James make the connections to previous content clear all the way. Highly recommended course!

By Oleksandr S

Nov 16, 2022

Outstanding and well-balanced course, great teacher, and an optimal workload. Passed the course with pleasure and highly recommended it.

By Ancil A

Mar 25, 2023

Covers all the basics and really easy to understand. Really well thought out curriculum.

By Elena K

Dec 6, 2022

Great review of the essential linear algebra! Thank you!

By uk3578

Oct 13, 2022

Loved it! Covered a lot in an efficient manner.

By Pallabi C

May 19, 2022

Please provide proper solns to all assignments

By Jolanta C

May 25, 2022

great course, highly recommnended

By Jason D

Jul 9, 2022

Excellent class for review!

By Bouifden r

Oct 25, 2022

thank you very much.

By Philip R

Mar 10, 2023

Great instructor!!!

By Hoyeon K (

Aug 2, 2022

Very helpful