Chevron Left
Back to Linear Algebra for Machine Learning and Data Science

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

4.6
stars
1,775 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.

Filter by:

101 - 125 of 445 Reviews for Linear Algebra for Machine Learning and Data Science

By Rahul A

Mar 1, 2024

Amazing course. Learnt a lot. All thanks to the Coursera for providing me with Financial Aid which allowed me to have full access to this course and have some real world experience of Machine Learning through the Labs. I look forward to continue with Calculus for ML.

By Mudit M

Apr 18, 2023

One should enroll in this course to explore the fundamentals and practical applications of Linear Algebra, even if you received a good grade in college but never learned it. I never expected to learn Linear Algebra the way Luis Serrano teaches it in this course.

By Hợp N X

Dec 18, 2024

"Not just dry formulas and numbers. The course provides many practical examples, helping to understand the essence of the problem: Why does this formula exist? What is it used for? Heartfelt thanks to DeepLearning.AI and Professor Luis Serrano. 100 stars."

By Mushfique A

Jun 6, 2024

Great course for a good enough intro into some key concepts. Accompany this with 3Blue1Brown videos on YT and you will learn a lot. I particularly liked the Eigen-stuff links to PCA, helped me understand the core basis of the calculations for PCA.

By Wajid I

May 24, 2023

Great course to work on some of the basic and necessary topics which are prerequisite to machine learning and data science. Instructor explained the topics in a simple words and visualized the topics which made the topics easy to insight.

By Kamlesh S

Nov 21, 2024

Sometimes the instructor's explanation does not seem to be clearer, but I guess since this is an intermediate course and I being a complete beginner. Anyways the course is great, helped me understand and recall so many algebric concepts.

By Sheikh I

Aug 1, 2024

Excellent course! It's essential to have a basic understanding of programming, especially arrays to better understand the programming part of the course. I want to upskill myself, and this course is the stepping stone in Data Science

By Ravikumar V

Oct 25, 2024

Excellent course to deeply understand the concepts of linear algebra as applicable to ML.Especially the coding exercises really drill it in. The instructor is amazing. I am looking forward to completing the specialization.

By Amr S

Dec 17, 2023

Luis Serrano is an amazing instructor, a fantastic mathematician, and a programmer. He can explain complex concepts easily and clearly. I enjoyed every bit of the course. Thanks, Luis, Andrew, deeplearning.ai, and Coursera

By Moetasim R

Apr 27, 2024

An absolutely wonderful course. I spent months on end trying to finish Gil Strang's introduction to linear algebra MIT course with no avail. That's why I greatly appreciate the conciseness that this course offers.

By Bertrand R

Jun 29, 2024

Very well done! All the foundational math concepts are very well presented, explained, and illustrated at the appropriate pace (for me). The teacher is very clear and engaging. The Jupyter notebooks are great.

By Praveen K M

Apr 17, 2024

Linear Algebra for Machine Learning and Data Science is an exceptional course. With clear explanations and hands-on exercises, it's a must for anyone looking to excel in machine learning and data science.

By Ash B

Mar 24, 2023

This course is very well organised The tools and programming assignments are very instructive. I am going to continue working on a few project to consolidate my learning and continue with further courses.

By Souvik

Dec 13, 2023

An insightful course into the inner workings of some of the technology of today, like YouTube's recommendation algorithm, or Google's PageRank algorithm, and how matrices and vectors are deeply involved.

By Haider A

Jun 11, 2023

Best course ever for Machine Learning. I appreciate the efforts of all who made that course so focused. Stay blessed the whole team and HEC Pakistan for giving me such an amazing opportunity of learning.

By Tianqi Y

May 15, 2023

Relatively basic. But if you have already learn Linear Algebra before, and wanna review quickly, or just wanna start to learn machine learning or deep learning. This course will be a suitable option.

By GUILLERMO D

Nov 2, 2024

The course was awesome! I finally got to understand how neural networks work, I had no idea calculus would help create these! The course was very clear, specially if you know calculus.

By Artinm89

May 25, 2024

I enjoyed this course I've learned how to solve systems of equations, matrices, and more. I've learned how to implement them using Python and how some machine-learning algorithms work

By Amanat U M

Oct 8, 2023

Great course and excellent instructor. All the concepts are explained in details with visual concept. There are also some coding labs so that we can implement what we have learnt.

By Larry M

Feb 8, 2024

Great course. Although I studied Linear Algebra many years ago in Engineering and Physics, it was an excellent refresher. The instructor really tied things together well.

By Cat W

Jul 13, 2024

Very fun intuitive way to learn Linear Algebra. Mr. Serrano gave me an understanding of what the concepts truly mean and why which I have never had before. Thank you!

By Rahul K

Aug 23, 2023

This course has given me new confidence to develop a mathematical mindset. After decades in data engineering, I am starting my new role in Machine Learning and AI.

By eliezer l n g

Feb 13, 2024

I'll really recommend to anyone eager to acquire the basic requirements for Machine Learning and Deep Learning. It was fun to learn with very practical exercises

By 莊子儀

Jan 13, 2024

This class employs straightforward examples and visualizations, aiding me in grasping the key concepts more efficiently. I thoroughly enjoyed this course.

By Mohammad O A

Oct 19, 2023

before this course, I was just in jungle by not knowing anywhere, but this course opens my eyes and it makes everything clearer at the foundational level.