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Learner Reviews & Feedback for Linear Algebra for Machine Learning and Data Science by DeepLearning.AI

4.6
stars
1,730 ratings

About the Course

Newly updated for 2024! Mathematics for Machine Learning and Data Science is a foundational online program created by DeepLearning.AI and taught by Luis Serrano. In machine learning, you apply math concepts through programming. And so, in this specialization, you’ll apply the math concepts you learn using Python programming in hands-on lab exercises. As a learner in this program, you'll need basic to intermediate Python programming skills to be successful. After completing this course, you will be able to: • Represent data as vectors and matrices and identify their properties using concepts of singularity, rank, and linear independence, etc. • Apply common vector and matrix algebra operations like dot product, inverse, and determinants • Express certain types of matrix operations as linear transformations • Apply concepts of eigenvalues and eigenvectors to machine learning problems Many machine learning engineers and data scientists need help with mathematics, and even experienced practitioners can feel held back by a lack of math skills. This Specialization uses innovative pedagogy in mathematics to help you learn quickly and intuitively, with courses that use easy-to-follow visualizations to help you see how the math behind machine learning actually works.  We recommend you have a high school level of mathematics (functions, basic algebra) and familiarity with programming (data structures, loops, functions, conditional statements, debugging). Assignments and labs are written in Python but the course introduces all the machine learning libraries you’ll use....

Top reviews

NA

Jun 17, 2023

Very visual and application oriented and gives the context for machine learning and where linAL is applied in PCA and neural networks. The structure is really byte sized and fun to work with.

SP

Jul 26, 2023

This course is truly exceptional for individuals eager to strengthen their grasp of Linear Algebra concepts, paving the way for a deeper understanding of machine learning and data science.

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326 - 350 of 434 Reviews for Linear Algebra for Machine Learning and Data Science

By Arturo

Aug 10, 2023

The videos and theory are great, very edible for a beginner. I can not say the same for the programming modules that I found confusing. I often used other resources to understand the concepts and solve the problems. However, I recommend this course.

By Regan B

Jun 2, 2023

The only issue I has was that I am not a super experienced coder and sometimes I got stuck with simple parts in the workbook. More resources to help with the coding aspect would be nice but overall I learned a lot. Even though the struggling bits.

By Navaneeth

Apr 4, 2023

The course was excellent in terms of teaching, practice quizes and Assignment Quiz.

The only problem is the programming assignment where some of the application oriented concepts are not familiar to me and don't know how exactly few codes worked.

By Anas A

Jun 10, 2023

Excellent course for introduction to Linear Algebra. However, the important part which is Eigen vectors, was not very well explained, and should have had given more time in my opinion which would have developed better understanding about it

By Yadava K S

Jun 18, 2024

Learned the math behind Deep learning, which is essential for understanding why the algorithms work, the last assignment could have been improved a little bit, it seems kind of a rush while working on it, keeping track of all the concepts.

By Mohamad H J

Oct 9, 2023

I like this course because of the high quality in teaching linear algebra and Numpy to solve some problem . Also I learned Matrix as well as and I'm glad to participating in Linear Algebra for Machine Learning and Data Science course .

By Hugo S

Nov 18, 2023

There are some errors on prompts and notebooks that made it difficult to understand some topics (until I get that the error was not being made by me). But in general, it was an excellent experience for me.

By Eligiusz M K

Feb 12, 2023

I am grateful for this course. However, IMHO, eigenvalues and eigenvectors could be explained in a more clear way. I would consider revising the last two pieces of video and recording them again.

By Akram M

Apr 20, 2023

it's was a great experience and the explanation was easy to understand. I want to thank everyone who works on this course. but I have an suggestion that labs supported with visual content like videos

By Nathan L

Jul 22, 2023

Some stuff left unclear & issues in some notebooks, otherwise great, I appreciated all the graphs explanations that made the course more understandable than when I had learned it at school

By Fahad H

Jun 22, 2023

A bit more detail into the complex topics of eigen values and eigen vectors would have been helpful. Also notebooks could have been oriented more towards the practical use of the concepts.

By Ra‚ K

Sep 23, 2023

I enjoyed the course very much but I found that week 4, especially the Eigenvalues and Eigenvectors explanation were not complete. This section can be definitely improved.

By Laure P K

Mar 31, 2023

Well explained and well paced. I had more trouble at the end with the Eigenvectors series. Since I had no prior programming, I did not do well with the Python labs.

By Parsa J

Nov 29, 2023

Great course with easy to understand material but it doesn't have any videos in programming lab section and is confusing in some parts in the beforementioned labs.

By Wafa A

Feb 7, 2023

I face some difficulty at the python part, since I have a tiny knoladeg at that part other than this every thing was really good! I enjoyed the course.

By Thokachichu T

Jun 16, 2023

Opened my eyes about the concepts i've learned in my UG studies...which i've been wondering how to implement practically, especially in ML and DS : )

By Cheater F

Jul 7, 2023

It's a great course with professional professors but there is one problem i hoped they made lab lessons videos but overall I loved it.

By Jathavan S

Jan 6, 2024

Good course, programming assignments were partially too easy. Portion around eigenvalues and eigenvectors appears to be a bit rushed.

By Douglas L

Oct 5, 2023

The course was excellent – clear videos with great content, and the problems were set at a good level, as were the programming labs.

By Emmanuel M M B

Jul 16, 2023

The eigenvalues and eigenvectors week is not clear and seems to have been rushed over. Otherwise the other weeks were clear.

By Arjun N

Jul 23, 2024

He was confusing at time but the basic revision of all these concepts and how it links to machine learning was helpful .

By rifqi a

Oct 9, 2024

the lesson is insightful but also a little bit difficult. maybe I need more time to rewatch the video to understand

By Putri R N M

Mar 19, 2024

I'm overwhelmed at coding sections, I'm soo confused that i started crying, but overall, that was great experience.

By Антоніна Т

Aug 1, 2024

sometimes it's hard to understand, but it's really cool! Thank you to everyone who helped to create this course!

By Abraham O

Oct 23, 2023

It's hard but I loved it. I would have preferred the instructor did more labs or a video of them doing the labs.