Dec 23, 2018
Professors teaches in so much friendly manner. This is beginner level course. Don't expect you will dive deep inside the Linear Algebra. But the foundation will become solid if you attend this course.
Apr 01, 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.
автор: Kunal A•
May 01, 2020
It was an awesome experience to learn how algebra can be conveyed through a computer code. The lecturers at Imperial college shared co-operative videos of learning. Coursera's subscription also helped a lot!
автор: Shihab S•
Apr 24, 2020
I would like to recommend every CS students to take this course to feel the essence of Linear Algebra. Well understandable couse it is and also the teachers are great and explaination was too understandable.
Sep 26, 2019
Sooooooperb course! The intuition developed by the professors was so so so magnificent that, you can apply this knowledge anywhere. Physics, signal processing and data science. Enjoyed the course throughout!
автор: Noor A•
Jul 05, 2019
Great course. Had a lot of fun building my intuition of Linear Algebra. With the unique way its taught id say its a must course for any bachelor's student who wants to get into the world of machine learning.
автор: Akshay L•
Jun 07, 2019
This is one of the best refresher course on Algebra for anyone who is getting into the field of Machine Learning and Data Science.
I learned so much from the course for these past couple of weeks.
автор: Mahmoud J S•
Sep 19, 2019
I wish I was taught all of math this way, The instructors were able to show the intuition of a lot of basic concepts and deepen my understanding of them. Highly recommend for anyone doing Machine Learning.
May 03, 2020
It's very interactive course for the beginner's who are good in python programming ,you can learn the standard techniques for machine learning and this course will show the path for your career interest's
автор: Jaiber J•
Apr 07, 2020
Excellent course, need to listen carefully to every sentence the instructor speaks or we miss something that will result in not solving the assignments. I liked the way the concepts are explained clearly.
автор: Tiong K L•
Dec 30, 2018
Hands down one of the best courses online. As a biology-trained student, I am glad that finally there is a course which explains linear algebra with such clarity that it does not remain a black box to me.
автор: Naveen K•
Jul 26, 2018
This course was awesome.Thanks a lot to all the lecturers for developing an intuitive understanding of Linear Algebra.I thoroughly enjoyed the course throughout .The journey was so exciting.Thanks a lot!!
автор: Saket S•
Mar 23, 2019
This course was very concise and to the point as far as the field of linear algebra in machine learning is concerned.I learned a lot and will also like to take up the next course of this specialization.
автор: Timothy L•
May 27, 2019
Thank you for providing this course. An advice would be to have the programming assignments start out with more guidance before letting the student do it. The Page Rank assignment for example was great.
автор: Yutong Z•
Apr 17, 2019
So great in general! But since it is not a pure maths course, some concepts are not explained in depth. It's a perfect course for self-learner because you can always go to the forum to look for answers.
автор: Om K•
Mar 22, 2020
The course is good because it doesn't just teach all of linear algebra like some other courses. It only teaches what is specific to Machine Learning which actually saves a lot more time than you think.
автор: Mahyar G•
May 31, 2020
A great course covering key aspects of Linear Algebra with the lecturers giving a good intuition about what's going on with the subjects.
(PS. I loved the sense of humor of Prof.Dye it was really fun!)
автор: Shuang J•
Nov 18, 2019
This course is not for people without any knowledge on Linear Algebra, but for those with who want to build intuitive understanding of how Linear Algebra works.
I particularly like Dave's instruction.
автор: Vitória C•
Jul 11, 2018
The content of the course is very relevant, and the instructors are really fun and helpful.My only suggestion is to upload revisions for each assessment, so we can understand what we are doing wrong.
автор: Bincheng W•
Mar 05, 2019
Satisfactory. Most satisfactory. Actually, this course is possibly the best linear algebra MOOC class in terms of instructor teaching style and how they pick and convey the most insightful concepts.
автор: David V•
Jun 25, 2019
This was a terrific course; the instructors' are passionate and knowledgeable about the course material, the assignments are engaging and relevant, and the length of the videos feels "just right".
автор: Pinas G•
Sep 14, 2019
Excellent course!! The Mathematics for Machine Leaning : Linear Algebra offered by the Imperial College of London it's a good step into building a strong foundation in the field of Linear Algebra.
автор: Jitender S V•
Jun 30, 2018
This is the BEST course if anyone wants to learn linear algebra for machine learning. Lectures are clear and very understandable and quiz questions are great, too. Thank you for this great course.
автор: ANURAG S•
Jul 12, 2019
It's a nice course but instructors should go in more details. It's mostly high school mathematics. I was expecting undergraduate level Linear Algebra. Otherwise it was a good learning experience.
автор: Peter H S•
May 09, 2018
Excellent course on the relevant parts of linear algebra for CS. Both instructors are great fun to watch and the assignments use up-to-date Python programming and Jupyter notebooks. Well done !!!
Apr 05, 2020
really good. i would have been fine with a slightly longer course that worked through more examples and alternative explanations in order to ensure more solid understanding of complex concepts.
автор: Archana D•
Mar 03, 2020
Brilliantly explained, loved the use of different marker which helped to understand better. Only one suggestion, if the summary has the mathematical equations/python equivalent would be helpful.