Master Linear Algebra 2020: The Complete Study Of Spaces
- 5.5 hours on-demand video
- 36 downloadable resources
- Full lifetime access
- Access on mobile and TV
- Certificate of Completion
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- Solve linear systems
- Understand matrix algebra
- Know how to find the determinant of any matrix
- Understand vector spaces and their properties
- Understand what a basis is and how to apply it
- Understand linear transformations
- Understand eigenvectors
- Understand norms
- Understand inner products
- Algebra from high school
- For inner products sections, we will give examples involving integrals...
Have you ever wanted to fully understand the fourth dimension? How about the fifth? How about a space that is infinite dimensional? This is likely the most applicable mathematics course ever. We cover in depth everything about dots, lines, planes, spaces, and whatever is beyond that. We detail special functions on them and redefine everything that you have ever learned. Prepare to have your mind blown!
Master and Learn Everything Involving Spaces
- Vector Spaces
- Linear Transformations
- How to Measure Space
- Definition of a Right Angle (The Real One)
- Inner-Product Spaces
- Eigenvalues and Eigenvectors
Linear Algebra Can Be Easy. Start Your Course Today!
This course includes everything that a university level linear algebra course has to offer *guaranteed*. This course is great to take before or during your linear algebra course. The book isn't enough - trust me. You will succeed with these lectures. It's hard to believe that such a difficult class can be made simple and fun, but I promise that it will be. This is a topic that is widely used with everyone, and can be understood. The reason that I succeeded in my linear algebra course is because I had a great professor, and you deserve one too! So what are you waiting for?
- Potential Engineers
- Potential Mathematicians
- Those interested in Algebra
It's hard to find a nice systematic way to compute a matrix inverse. Good news is, there is one. Hint: It's in this lecture.
Determinants barely change if you RREF a matrix. Here we prove why, and we show the fastest way of computing a determinant.
It's weird how infinite spaces can be defined by a couple of vectors. Here we go through what dimension is and show an example of a space that is infinite dimensional.