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In this course on Linear Algebra we look at what linear algebra is and how it relates to vectors and matrices. Then we look through what vectors and matrices are and how to work with them, including the knotty problem of eigenvalues and eigenvectors, and how to use these to solve problems. Finally we look at how to use these to do fun things with datasets - like how to rotate images of faces and how to extract eigenvectors to look at how the Pagerank algorithm works.
Since we're aiming at data-driven applications, we'll be implementing some of these ideas in code, not just on pencil and paper. Towards the end of the course, you'll write code blocks and encounter Jupyter notebooks in Python, but don't worry, these will be quite short, focussed on the concepts, and will guide you through if you’ve not coded before.
At the end of this course you will have an intuitive understanding of vectors and matrices that will help you bridge the gap into linear algebra problems, and how to apply these concepts to machine learning....

HE

8. Aug. 2021

the instrutors were too good and their explination for the concepts was to the point and it made me realize things in linear algebra I didn't know before although I studied it in school of engineering

CS

31. März 2018

Amazing course, great instructors. The amount of working linear algebra knowledge you get from this single course is substantial. It has already helped solidify my learning in other ML and AI courses.

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von Kamile D

•30. Juni 2021

I really enjoyed this course. Although the video material was quite dificult to comprehend at times, it was sensibly put together in short video batches and also with many tests in between that really heped to digest and fully understand the material.

von DASGAONKAR Y N

•12. Juli 2020

This was one of the best courses for linear algebra for a working professionals, students and researchers who want to brush up their skills as this course is very different from the regular book stuff.It was more practical with real world assignments.

von Loc N

•9. Jan. 2020

Awesome course! Entertaining and digestible, with great assignments despite some hiccups in file organization and a slight lack of response from admins (understandable because the course is old). It was so awesome that I had to go and tweet the profs.

von Lorenzo

•27. Sep. 2019

it's a very well structured and well taught course. The lecturers have the ability to keep the students interested in the subject and the various exercises at the end of each session are a very good way to find out where extra work/research is needed.

von Volodymyr C

•27. Jan. 2019

Clearly explained and key equations are derived with good step sizes. Quizzes and assignments are challenging (which is good!) and have high expectations for learners (which is really good for my motivation). Overall, I am really enjoying this course.

von Ion S

•3. Juni 2021

This course was perfect except for the last assignment. It took on average over double the time to complete (including for me), and I died multiple times :). Other than that the course helped me a lot with my understanding about matrices and vectors!

von Agamjyot C

•3. Juni 2020

A really nice course, I had already done a Linear Algebra module in the university. But that was mostly mugging up and not knowing what this is used for. This course's geometric interpretation of all topics, helped me a lot and give a lot of insight.

von Nut P

•25. März 2020

The presentation an way of teaching is excellence; however, the course should add more reference or additional source or materials for more in dept detail for the person who feel that the simplified explanation in the course are still not sufficient.

von Joshua N T

•16. Juni 2022

This is a great course and the various concepts were lucidly explained by the course tutors: David Dye and Sam Cooper. I had the opportunity to understand the reasons behind most things that were memorized during my undergrad studies. Thanks a lot.

von Steven J R

•25. Feb. 2021

So exhausted, but amazed how the computer managed to process this kind of things for us everyday!

The lecturer were so nice and the explanation was so clear and funny too, although there are several assignments (which on my opinion) is sooo hard :((

von Jonathan M

•10. Apr. 2020

Extremely helpful. I haven't taken a linear algebra class in almost 5 years and by going through these videos it helped me regain an intuition towards the subject. The videos do a good job of tying the material back to machine learning as a whole.

von Cyprien P

•3. Juli 2020

Great maths refresher content, with very useful 2D geometrics examples helping to build the intuition rather than just explaining the maths. I feel like I can understand this part of linear algebra now, and I know what to search for when I won't.

von Astankov D A

•16. März 2020

Great explanation of all the important things, with topical examples and practical tasks. Still, it seemed to me that the course was growing more and more complex exponentially by the end of it, so it was really hard to catch up starting week 4.

von Yiğit A T

•14. März 2021

The perfect class to either get introduced to the important parts of Linear Algebra or to brush up your skills. I would definitely suggest anyone take this course for the quality of the lectures, the delivery, and the fun programming exercises!

von Thomas F

•18. Apr. 2018

Highly valuable introduction to linear algebra. Maybe the programming assignments are far too easy, while some of the quizzes definitely are hard. And the best part of the course was to introduce www.3blue1brown.com with it's videos on youtube.

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von Randy S

•12. Mai 2020

A good mix of theory in videos, simpler practice problems to reinforce the learnings, and scalable applications in Python. Very much enjoyed the course and feel like I've learned a lot about linear algebra and the applications in data science.

von Ryan M

•10. Apr. 2020

I very much enjoyed the content of this class. The professor for the first 4 weeks was great! The professor for the 5th week seemed to move at a slightly faster pace with less in-depth instruction. His visual aids were pretty groovy though.

von Aleena T

•13. Sep. 2020

Excellent course for anyone who wants to know the nuances of Linear Algebra and its applications.The applications are not just mentioned,but one gets hands-on experience applying the concepts they learned,in code.Hats Off to the entire team!

von Shivam K

•26. Mai 2020

The course is really helpful to those seeking clarity on the concepts. Week 4 and 5 really will really demand your attention. Loved every single bit of this course.

Would be glad if course would have included more visualisation to play with.

von CHIOU Y C

•2. Jan. 2020

This is a good linear algebra course intro. May not be the one for who is looking for mathematical rigorous but it's enough for machine learning. Linear Algebra is important but not all topics and this course highlights the needed materials.

von Jaromir S

•30. Sep. 2019

I needed a quick refresh of my prior knowledge of linear algebra for my MSc course and I wasnt disappointed. I also appreciated the complementary python exercises and the effort to put the material into a context of a real world application.

von Someindra K S

•3. Jan. 2019

I got a lot of intuition about some fundamental aspects of linear algebra. Rest of courses on maths was very rigorous in terms of methods. This was more inclined towards applications in machine learning. I enjoyed the entire learning process

von Stefan B

•8. Apr. 2018

It was fun to work through the course. Sometimes it was challenging as it has to be. Now I have a much better understanding of the topic. Especially appreciated is the approach of the instructors to build intuition: it worked for me, thanks!

von Souvik G

•8. Feb. 2021

I have never visioned mathematics the way it was taught here. I believe every Engineer may he/she be a an ML engineer or not must take this course to just fall in love of mathematics. This course will inherently motivate you to dig deeper.

von Danilo d C P

•19. Juli 2019

I really enjoyed taking this course. I could review and learn for the first time some important topics for machine learning, in special the eigenvalues and eigenvectors classes. I'd like to thank the course's professors and collaborators.

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