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

4.5
stars
1,214 ratings

About the Course

Newly updated for 2024! After completing this course, learners 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 Mathematics for Machine Learning and Data science is a foundational online program created in by DeepLearning.AI and taught by Luis Serrano. This beginner-friendly program is where you’ll master the fundamental mathematics toolkit of machine learning. 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 plugins and visualizations to help you see how the math behind machine learning actually works. Upon completion, you’ll understand the mathematics behind all the most common algorithms and data analysis techniques — plus the know-how to incorporate them into your machine learning career. This is a beginner-friendly program, with a recommended background of at least high school mathematics (functions, basic algebra). We also recommend a basic familiarity with Python (loops, functions, if/else statements, lists/dictionaries, importing libraries), as labs use Python and Jupyter Notebooks to demonstrate learning objectives in the environment where they’re most applicable to machine learning and data science. If you are already familiar with the concepts of linear algebra, Course 1 will provide a good review, or you can choose to take Course 2: Calculus for Machine Learning and Data Science and Course 3: Probability and Statistics for Machine Learning and Data Science, of this specialization....

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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51 - 75 of 340 Reviews for Linear Algebra for Machine Learning and Data Science

By Hiếu V

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Feb 28, 2023

good

By Issa A

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Feb 19, 2023

This course was great! It provided me with a deeper understanding of several topics. I highly recommend it. However, I would have appreciated learning about matrix factorization and the application of linear algebra to linear regression as well, which was missing in this course.

By João S

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Jan 30, 2023

I missed some important concepts like Vector Projection and Matrix Calculus, just to exemplify some. I hope the other courses cover them.

By Ken K

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Feb 7, 2023

Lectures were excellent but some of the labs and and quizzes contained concepts not covered in the lectures.

By kewal k

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Feb 13, 2023

Eigen Vectors/Values and Transformations could have been explained better

By Samuel H

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Jan 29, 2023

Excellent intro to the fascinating world of Linear Algebra.

By nagesh d

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Mar 3, 2023

Although the course helped me stimulate interest in the right direction and helped me narrow down the context (from all the distractions online), yet this course did not help me construct a clearer intuition so needed to venture all on my own. Its almost like when a baby all of a sudden finds a new skill/trick/ability and amazes her/himself - at that very moment something happens deep in the brain that taunts the baby to explore further and deeper to hone that skill completely on her/his own - I miss that intuition from this course. Of course, on the other hand, I understand this is the best what you get for this price and for everything else you need to be Harvard educated.

By Borja F C

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Feb 26, 2023

I think a little more of a level would be great, it is always good to refresh basic concepts but the level for this course is maths reaaaally basics.

In my humble opinion, it looks like data scientists, deep learning researchers, machine learning engineers, and so on... do not really need to know maths to do an actual good job while it is totally the opposite the more maths you now the easier for you to understand when something is wrong.

Note here: maybe statistics for data science would be a great new course, and there you can start from the basics since statistics are typically pretty badly taught at schools.

By Scott A

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Apr 14, 2023

I feel I've learnt a decent amount of Linear Algebra from the course. Stars reduced as I had to turn to supplementary learning tools at times, and I would have preferred more practice labs.

By Jakub J

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Feb 20, 2023

Good course however too shallow.

By Abdelerahmane K

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Jul 14, 2023

one of the worst courses i ever took, maybe the worst. my problems in this course are the following: 1- the course material doesnt teach the required skills : as a person who started studying AI from a year, i felt the need to learn math deeply so i can understand more concepts in AI better, but this course doesn't even provide close to enaugh knwldge in linear algebra for AI, it's too short and the concepts are the basics 2-the lectures teach by example not by rule : here i mean that instead of teaching you the rules required and show you some examples on applying this rule, no , it just gives u approximation on the rule in yoour head by showing you 2-5 simple examples, and no enaugh generalization is mentioned or proof of any rule (m telling you most of the cases he doesn't even state the rule of a concept) 3-the code part is good for theory but terrible for application : unlike the videos, the markdowns of the code labs had good short paragraphs that explain the concept with it's rule, but the coding part was bad, i feel that i don't need to code the concept to confirm that i got it , and it's too long and easy 4-the quizes are either easy or impossible : cause the material of the video wasn't enaugh, some quizes are totally impossible to solve just by watching the videos unless you're a genuis and you could get some concepts that are derived and far from the concept in the video, specially in week 4, otherwise the quiz is easier much more than it should , graded quizes are quite good tho.

By Marko N

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Apr 26, 2023

The course is too difficult for a beginner, it's very fast paced for my liking.

By Brian G

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Feb 15, 2023

I am unable to find the course forums or any way to interact with the course instructors or other students. The "Discussion Forums" link in the left-side menu takes me to the Forums page which has three tabs: Posts for you, All forums, and Your activity. The "Posts for you" and "Your activity" tabs show "No posts yet" and are otherwise blank. The "All forums" tab is completely blank. There are no links to create a new post. Also, I received an email this morning entitled "How is your course experience so far?" that suggests posting in the "Discourse community," but there is no hyperlink to this community and I'm unable to find it. Lastly, there is a "Discuss" link above each course video which, when clicked, takes you to a page that reads "Oops! Looks like this thread isn't viewable or does not exist." Perhaps Coursera is experiencing technical trouble at the moment, but that still doesn't explain why the email doesn't link to the Discourse community.

By Mohammad J

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Jan 9, 2024

My recommendation for those who are considering paying for this specialization is to search up 3Blue1Brown and learn from him FOR FREE. The concepts themselves are not bad albeit being a little shallow and surface level. The python labs are a joke because the auto grader does not work and no one in the community will help you resolve it.

By SHAIK M P

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Jun 24, 2023

I am grateful to complete "Linear Algebra for Machine Learning and Data Science" course with 100% grade. This course provides all the concepts which is required for machine learning and data science. It is a course that focuses more on the intuition part rather than just formulas. With the help of this course, I understood linear algebra in a completely different way than I did during my graduation. I highly recommend everyone who has an interest in data science to enroll in this course. I would like to express my gratitude to Andrew Ng and Luis Serrano for providing this wonderful course.The course covers a wide range of topics, including: System of linear equations, singularity, determinants, rank, linear dependency, row echelon form, vectors, dot product, orthogonality, linear transformation, eigenvalues, and eigenvectors etc.Additionally, the course covers the "linalg" module from Numpy Python library, which is commonly used for linear algebra computations. It also includes programming assignments that allow students to apply the concepts learned in practical coding exercises.

By Sridhar V (

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Jun 26, 2023

It has been intriguing to me how Linear Algebra (non-singular systems, linear transformations, vectors, matrices — dot products, inverse, determinants, eigenvalues, and eigenvectors) plays a crucial role in understanding and developing machine learning (ML) algorithms. And how Linear Algebra provides a framework for representing and manipulating data, as well as the mathematical foundations for many ML techniques. 

Thanks to Prof. Luis Serrano and the Deep Learning.AI team for making the course so easy to understand with a common sense approach. Sure, it has satiated the hunger of Business Analytics enthusiasts like me. 5 out of 5 for the course and the impeccable delivery. It has sparked an urge in me to learn and practice more, to transfer the knowledge to my students, and to discuss with like-minded people.

P.S: Thanks to Lucas Coutinho for patiently attending to my queries and guiding me along wrt the Lab exercises.

By Maryam R

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Apr 28, 2023

I found the Linear Algebra for Machine Learning and Data Science course to be an excellent resource for improving my understanding of linear algebra. The course covers a wide range of topics, including matrices, vectors, and eigenvalues, and the material is presented in a clear and concise manner.

One of the only downsides of the course was the lab sections, which were challenging to follow without any accompanying lectures. However, with enough time and effort, I was able to work through the labs and gain a deeper understanding of the course material.

Overall, I highly recommend this course to anyone looking to improve their understanding of linear algebra for machine learning and data science. Thank you to the course creators for putting together such an excellent resource.

By Amal N

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Jul 27, 2023

This course is exceptionally suited for beginners starting their Data Science journey. It provides a comprehensive introduction to Linear Algebra, presented in a highly accessible manner. The instructor's teaching style is exceptional, offering clear explanations and maintaining engaging content. Furthermore, the use of effective visualization tools greatly enhances the understanding of the concepts.

What truly sets this course apart is the practicality of the assignments. DeepLearning.AI impressively bridges the gap between basic mathematics and real-world applications, fostering intuition and interest among aspiring learners entering this initially daunting domain. The practical approach makes the course truly amazing and highly recommended.

By Agnes H

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Apr 6, 2023

It was fantastic! The course was well-structured and covered many, complex topics in a clear way. The instructor was very engaging, making complex concepts easy to understand. The best part was using visuals to explain the theories and practical examples, I wish all courses would use such visuals! I really enjoyed the practical examples and coding exercises. Especially as the code was explained. I highly recommend this course to anyone looking to improve their understanding of linear algebra for machine learning. I am looking forward to completing any other DeepLearningAI course.

By HHCNAY

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Mar 9, 2023

Through several online platforms, I've learned about LA to varying degrees in the past, including: MIT opencourseware course taught by professor Gilbert Strang, YouTube channel 3Blue1Brown, and WolframAlpha. Each has provided a different learning perspective, all very useful. All of that background knowledge was expanded on, refreshed, consolidated and applied to the field of ML in a very practical and hands-on way in this course. Thank you to the folks at DeepLearning.AI for making this content available to all.

By Mateo R A

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Sep 23, 2023

Great course!. Explanations go from a more general or intuitive perspective to the mathematical concept, which in turn is explained through different ways such as geometrically (graphically) to do operations on equations, matrices, vectors,.. Week after week is presented the machine learning context and the reason why that linear algebra concept is important in any particular application. I really enjoyed also the real examples from the quizes that give even more context and a better understanding of the topics.

By antoni l

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Jun 9, 2023

I really like the simplicity of the video and visual cues. It really helps us to learn. On thing I need to constructively criticize is the topic of eigenvalue and eigenvector. I believe more example is needed and more detail on how to calculate eigenvectors itself. The question in the quiz is the 3x3 matrix with repeated eigenvalue, which is not really explained. I have to resort to other youtube video just to understand the techniques to solve it. Other that this, this is really good course

By Asad B

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Jun 16, 2023

The course content was comprehensive and exceptionally well-structured, covering a wide range of fundamental concepts and techniques in linear algebra. The clear explanations, engaging examples, and interactive exercises made even complex topics accessible and enjoyable to learn. I truly appreciated the thoughtful progression of the course, starting from the basics and gradually building up to more advanced concepts.

By Mohammad S

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May 22, 2023

A beneficial course for beginners. These concepts are covered in school years but this course is an excellent source to recover what one might have forgotten. The course starts slow and speeds up later on. I prefer to cover the starter basics at a faster pace and spend more time and lectures on the latter part which is more complicated.

I can't wait to finish the second module.

By Vishwajeet K

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Jan 5, 2024

I have learned every concept of Linear Algebra needed for Machine Learning and Data Science and Deep Learning and all other fields included in Artificial Intelligence. With theoretical knowledge and practical implementation using Python's NumPy library, I feel very confident and ready to dive deep into the fields of Machine Learning and Deep Learning.