This was basically a revision for me, but I really enjoyed the course, especially the way Mr. Luis Serrano is approaching and visualising the concepts. It's also nice to always relate each concept to real-world application. Learning Maths this way is much more funny and easy to understand.

I have discovered many things about linear algebra with this course. The lectures were good and clear, the exams were not too difficult and I was able to finish this course at my own pace. I recommend this course especially for those who want to know more about linear regression.

This is a great course that balances linear algebra theory and application. Prof. Luis Serrano excels at building intuition about the various elements and methods in the course through excellent visualizations and clear exercises. Additionally, the content is very well organized.

Very informative, this gives a good understanding of the concepts of matrices and vectors and why it is important in machine learning. This course ends with the concept of PCA, a popular technique used in ML to transform high-dimensional data to low-dimensional data. Thanks!!

The course material on Coursera is excellent. Delving into the concepts and utilizing the provided resources for further research significantly enhances one's understanding of the topics. This comprehensive learning experience truly enriches the overall educational journey.

Perfect pace and level of difficulty. Coding assignments are really well structured. Material shared is easy to be used as a reference in future. Time was well spent in refreshing my linear algebra knowledge and learning about how to use NumPy to handle linear algebra.

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.

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.

"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."

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.

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.

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.

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

Great and illustrative explanations! I was looking for a course to start in the world of mathematics for ML, I've learned some applications of linear algebra in ML and have realized its the incredible potential in data science.

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.

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

Awesome Course ..... Nice examples Only the PCA was better to be postponed after the probability course instead for spending a lot of time understanding some concepts just to understand an application (Covarience)

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.

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.

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.

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.

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.

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.

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.

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.