
Vector Calculus Series 4 - Integral Advanced
tkn
This course will help you build your knowledge of advanced integration of multivariable functions.
Intermediate
Integral Differential
This course covers introduction to linear algebra, and you can master introduction to linear algebra through the lectures.

Understanding and solving linear equations
Basic operations of matrix algebra
Determinant calculation and applications
Calculation and use of eigenvalues and eigenvectors
Solving orthogonality and least squares problems
Understanding symmetric matrices and quadratic forms
Advanced matrix decomposition and inverse algorithms
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🌿 Are you an engineering student? Are you a former engineering student? Are you an engineer? Are you a graduate student?
❤️ Then you absolutely must master Introduction to Linear Algebra!
🌿 Are you taking an introduction to linear algebra class in English, but you can't understand what the professor is saying?
❤️ This lecture is for you!
🌿 Do you want to study college math as a hobby? Or maybe you just want to learn it?
❤️ Start studying now! Your perspective on the world will change a little!
🌿 Are you curious about the level of college mathematics taught at KAIST?
❤️ This rare opportunity is for you!
Most engineering students learn introduction to linear algebra in their first or second year of undergraduate school.
But at the time, I didn't realize how important it was and I tended to just listen to it. (I did the same thing😅)
It didn't take long for linear algebra to become necessary in engineering.
But when you open your textbook again and try to study, you don't know where to start?
Now you don't have to flip through English textbooks to study linear algebra.
The most fatal obstacle to studying linear algebra is, paradoxically, 'language'.
All materials and lectures are in English, making it difficult to learn quickly.
This lecture is for those people who want to organize it in an easy-to-understand way in Korean.
This course is designed to help you master the introduction to linear algebra required for engineering mathematics. 

Who is this course right for?
Students learning linear algebra for the first time
Engineering and Computer Science majors
People interested in data analysis and machine learning
People who want to build a solid foundation in mathematics
People who want to learn theory and practice in a balanced way
6,299
Learners
176
Reviews
387
Answers
4.7
Rating
7
Courses
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전문분야 (+좋아하는 분야) 👨🎓
출신학교
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링크
All
37 lectures ∙ (19hr 6min)
All
110 reviews
4.7
110 reviews
Reviews 3
∙
Average Rating 4.0
Edited
5
I'm writing this review after completing 75% of the course. I'm a liberal arts graduate who gave up on math. I'm taking this course because I want to go to graduate school for data analysis. It might be different for everyone, but it was so difficult for me that I think I replayed each lecture about ten times. Each lecture is relatively short at 30-40 minutes, but there were times when I spent almost an entire day trying to understand just one lecture. Honestly, no matter how well the instructor explains it, the linear algebra content itself is so abstract... In the end, I had to go back and review the lecture materials on my own and replay the instructor's explanations several times. When I first listened, I thought "What on earth is he talking about?" but after replaying it about ten times, I could understand what he was saying. I barely, barely finished up to eigenvalues and vectors. I really thought I was going to throw up. Now that I'm finishing this, I have this baseless confidence that I'll be able to take any math course. However, the lecture slides have a black background... which made it hard to take notes, so that was quite disappointing.
If it's fifteen times... I respect you. I also get strength.
It seems like you can do whatever you want.. Since this is the first lecture I've made, there are probably a lot of parts that I couldn't explain easily. Still, thank you for being so kind!
Reviews 2
∙
Average Rating 5.0
5
I am leaving a review after taking the course twice and once in reverse. For reference, I took 'Linear Algebra Using Python - Using SciPy' before taking this course. If you master the content of this course, you will be able to do the following two things. - 1. Understand the mathematical background of the 'Linear Algebra Using Python - Using SciPy' course The course above can teach you how to use various functions even if you do not have a good understanding of linear algebra, but if you listen to it after understanding the content of the linear algebra course, you will be able to better understand why the function is used. - 2. Understand the 'MIT 18.06 Linear Algebra, Spring 2005' course on YouTube You can easily watch most of the course. Looking back, I think the reason I didn't understand Professor Strang's lecture at first was because he taught it so intuitively that it was difficult. After taking Professor Cho Beom-hee's Introduction to Linear Algebra, I understood it well. Personally, I found the part explaining Matrix space and various applications in 'MIT 18.06 Linear Algebra, Spring 2005' a bit difficult, but I was able to enjoy the rest of the content. Thank you for the great lecture.
Thank you so much for the detailed course review. The course I first created may have some shortcomings, but I am proud that it is developing with the help of students. I am also very happy that it is helpful to someone. After the courses I create in the future are somewhat complete, I will supplement the shortcomings and areas for improvement of the Introduction to Linear Algebra course to make it a more advanced course. Have a good day, and please feel free to ask questions or let me know if you see any areas for improvement. ㅎㅎ Thank you.
Reviews 6
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Average Rating 5.0
5
For those who are thinking about it..... I recommend it While studying machine learning, I found a linear algebra lecture and ended up taking it... I finished it today~ㅋㅋ First of all, it's fun. If you ask a question by email, they answer quickly (they really answer quickly, they're awesome~) I've taken many other domestic/international online lectures, but this is the cleanest. Please make lots and lots of probability theory, optimization, etc.!!!:)
I will work hard to make a fun course!! Thank you ^^
Reviews 1
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Average Rating 5.0
Reviews 1
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Average Rating 5.0
5
I'm in tears listening to SVD... It's just a great class... ;ㅁ;
Thank you so much. I almost shed tears of emotion when I read the course review. Haha. I hope the course was helpful. Then have a good night! :)
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