Linear Algebra for Data Science & Machine Learning A-Z 2024

Linear Algebra for Data Science, Big Data, Machine Learning, Engineering & Computer Science. Master Linear Algebra

4.55 (740 reviews)

Udemy

platform

English

language

Career Development

What you will learn

Fundamentals of Linear Algebra and how to ace your Linear Algebra exam

Basics of matrices (notation, dimensions, types, addressing the entries etc.)

Operations on a single matrix, e.g. scalar multiplication, transpose, determinant & adjoint

Operations on two matrices, including addition, subtraction and multiplication of matrices

Performing elementary row operations and finding Echelon Forms (REF & RREF)

Inverses, including invertible and singular matrices, and the Cofactor method

Solving systems of linear equations using matrices and inverse matrices, including Cramer’s rule to solve AX = B

Properties of determinants, and how to perform Gauss-Jordan elimination

Matrices as vectors, including vector addition and subtraction, Head-to-Tail rule, components, magnitude and midpoint of a vector

Vector spaces, including dimensions, Euclidean spaces, closure properties and axioms

Linear combinations and span, spanning set for a vector space and linear dependence

Subspace and Null-space of a matrix, matrix-vector products

Basis and standard basis, and checking if a set of given vectors forms the basis for a vector space

Eigenvalues and Eigenvectors, including how to find Eigenvalues and the corresponding Eigenvectors

Basic algebra concepts ( as a BONUS)

And so much more…..

Why take this course?

DO YOU WANT TO LEARN LINEAR ALGEBRA IN AN EASY WAY?

Great!

With 22+ hours of content and 200+ video lessons, this course covers everything in Linear Algebra, from start till the end!

Every concept is explained in simple language, and Quizzes and Assignments (with solutions!) help you test your concepts as you proceed.

Whether you're a student, or a professional or a Math enthusiast, this course walks you through the core concepts of Linear Algebra in an easy and fun way!

HERE IS WHAT YOU WILL LEARN:

· Fundamentals of Linear Algebra and how to ace your Linear Algebra exam

· Basics of matrices, including notation, dimensions, types, addressing the entries etc.

· Operations on a single matrix, e.g. scalar multiplication, transpose, determinant, adjoint etc.

· Operations on two matrices, including addition, subtraction and multiplication

· Performing elementary row operations and finding Echelon Forms (REF & RREF)

· Inverses, including invertible and singular matrices, and the Cofactor method

· Solving systems of equations using matrices & inverse matrices, including Cramer’s rule to solve AX = B

· Performing Gauss-Jordan elimination

· Properties of determinants and how to utilize them to gain insights

· Matrices as vectors, including vector addition and subtraction, Head-to-Tail rule, components, magnitude and midpoint of a vector

· Linear combinations of vectors and span

· Vector spaces, including dimensions, Euclidean spaces, closure properties and axioms

· Subspace and Null-space of a matrix, matrix-vector products

· Spanning set for a vector space and linear dependence

· Basis and standard basis, and checking if a set of given vectors forms the basis for a vector space

· Eigenvalues and Eigenvectors, including how to find Eigenvalues and the corresponding Eigenvectors

· Basic algebra concepts (as a BONUS)

· And so much more…..

HERE IS WHAT YOU GET IN THE COURSE:

Video Lessons: Watch over my shoulder as I explain all the Linear Algebra concepts in a simple and easy to understand language. Everything is taught from scratch, and no prior knowledge is assumed.

Solved Examples: Every topic is explained with the help of solved examples, from start to end. This problem-based approach is great, especially for beginners who want to practice their Math concepts while learning.

Quizzes: When you think you have understood a concept well, test it by taking the relevant quiz. If you pass, awesome! Otherwise review the suggested lessons and retake the quiz, or ask for help in the Q/A section.

Assignments: Multiple assignments offer you a chance for additional practice by solving sets of relevant and insightful problems (with solutions provided)

By the end of this course, you'll feel confident and comfortable with all the Linear Algebra topics discussed in this course!

WHY SHOULD YOU LEARN LINEAR ALGEBRA?

· Linear Algebra is a prerequisite for many lucrative careers, including Data Science, Artificial Intelligence, Machine Learning, Financial Math, Data Engineering etc.

· Being proficient in Linear Algebra will open doors for you to many high-in-demand careers

WHY LEARN LINEAR ALGEBRA FROM ME?

I took this Linear Algebra class at University of Illinois at Urbana Champaign, one of the Top-5 Engineering Schools in the country, and I have tried to follow the same standards while designing this course.

I have taught various Math and Engineering courses for more than 10 years at schools across US, Asia and Africa. I strongly believe that I have the ability to breakdown complex concepts into easily understandable chunks of information for you!

I provide premium support for all my students - so if you ever get stuck or have a question, just post it to the course dashboard and I'll be there to help you out in a prompt and friendly way!

My goal is to make this the best Linear Algebra and Math course online, and I'll do anything possible to help you learn.

HERE IS WHAT STUDENTS SAY ABOUT THIS COURSE:

“I thoroughly enjoyed this course. I needed to get a better understanding and a good base of Linear Algebra for Data Science and Machine Learning and Kashif absolutely delivered. This is definitely a Zero to Hero course on Linear Algebra in my opinion, and would highly recommend this to anyone who is on the same path as I am. Nothing but appreciation for this author.” – I. Valderrama

“Wish I had found this earlier” - Dan

“Great explanations. Solid teaching” - J. P. Baugh

“Excellent course! The course material is really good, explanation is really clear and every new concept is provided with examples that make the experience even better! The instructor always takes the time to answer questions poster in Q&A. New material is constantly added to course. Thank you!” – K. Geagea

YOU'LL ALSO GET:

· Lifetime access to “Complete Linear Algebra for Data Science & Machine Learning”

· Friendly support in the Q&A section

· Udemy Certificate of Completion available for download

· 30-day, no-questions-asked, money back guarantee

ENROLL TODAY!

Feel free to check out the course outline below or watch the free preview lessons. Or go ahead and enroll now.

I can’t wait for you to get started with Linear Algebra.

Cheers,
Kashif

Screenshots

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Our review

--- **Course Review: Comprehensive Introduction to Linear Algebra** **Overall Rating:** 4.55 **Pros:** - **Thorough Explanation:** The instructor does an excellent job of explaining each concept in a stepwise order, making it easy for beginners to follow along. (Reviewer #2) - **Pace for Beginners:** The pace is comfortable and suitable for those who are new to the topic of linear algebra. (Reviewer #3) - **Real-World Application:** The course provides a solid foundation for understanding linear algebra, which is crucial for data science and machine learning applications. (Reviewer #5 & Reviewer #10) - **Comprehensive Overview:** Offers a comprehensive overview of linear algebra, covering all the necessary topics in great detail. (Reviewer #9 & Reviewer #14) - **Easy to Understand:** The course content is taught in an easy, interesting, and comfortable manner, with lots of examples to solidify understanding. (Reviewer #13 & Reviewer #17) - **Practical Examples:** Some reviewers appreciate the inclusion of practical examples that help connect linear algebra concepts to real-life situations and data science applications. (Reviewer #2, #10, #18) **Cons:** - **Lack of Real Examples:** Several reviewers pointed out a lack of practical examples, especially in relation to data science and machine learning, which could make the course more applicable for those fields. (Reviewer #7 & Reviewer #20) - **Redundant Content:** A few reviews mention that some topics were repeated, which may unnecessarily extend the course duration for some learners. (Reviewer #12) - **Bonus Material Irrelevant:** Some learners found the bonus material to be non-algebraic and not directly related to the core aims of the course, suggesting that it should not be mandatory to complete the course or obtain a certificate. (Reviewer #18) - **Title Misleading:** The course title may lead some students to expect more direct applications to data science and machine learning than are delivered. (Reviewer #9 & Reviewer #19) - **Missing Fundamentals:** A few reviewers suggest that foundational topics like calculations for determinants and inverses could be better explained, with a preference for seeing actual numbers rather than variables. (Reviewer #4 & Reviewer #15) - **Pacing Issues:** While the pacing is generally praised, some learners find the course too slow after having dropped another rushed course. (Reviewer #6) - **Vector Explanations:** Some learners feel that the explanations for vector concepts could be improved and that more exercises would be beneficial. (Reviewer #14 & Reviewer #21) - **Advanced Examples Needed:** To enhance the learning experience, reviewers suggest including more advanced level examples that relate to machine learning. (Reviewer #7 & Reviewer #22) **Final Thoughts:** This course offers a solid introduction to linear algebra with a focus on thorough explanations and a pace suitable for beginners. It is particularly well-received for its foundational content in relation to data science and machine learning. However, learners have pointed out areas where the course could be improved, including the incorporation of more practical examples and advanced topics that directly relate to real-world applications in data science and machine learning. The pacing may also need adjustment for learners who are accustomed to faster-paced courses. Overall, this course serves as a strong foundation but has room for enhancements to fully meet the expectations set by its title and audience's needs. --- **Note:** The reviewer comments have been synthesized to provide a balanced overview of the course's strengths and areas for improvement. The ratings and feedback from individual reviewers have been used to inform this summary.

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