Linear Algebra
part 3 of 3

A total of 50 hours of lectures

This is an academic level course for university and college engineering. Due to its size, it is divided into three parts. This page describes the third of those three parts.

Level - Intermediate

  • High-school and college mathematics (mainly arithmetics, some trigonometry, polynomials)
  • Linear Algebra and Geometry 1 (systems of equations, matrices and determinants, vectors and their products, analytic geometry of lines and planes)
  • Linear Algebra and Geometry 2 (vector spaces, linear transformations, orthogonality, eigenvalues and eigenvectors, diagonalization)
  • Some basic calculus
    Basic knowledge of complex numbers (this course contains a short introduction to complex numbers)

Curriculum

Make sure that you check with your professor what parts of the course you will need for your exam. Such things vary from country to country, from university to university, and they can even vary from year to year at the same university.

Linear Algebra, part 3 of 3

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Get the outline

A detailed list of all the lectures in part 3 of the course, including which theorems will be discussed and which problems will be solved. If you are looking for a particular kind of problem or a particular concept, this is where you should look first.

Get Linear Algebra part 3 on Udemy

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Course Objectives & Outcomes for part 3

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How to solve problems in linear algebra and geometry (illustrated with 144 solved problems) and why these methods work.
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Use diagonalization of matrices for solving various problems from different branches of mathematics (ODE, dynamical systems).
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Work with geometric concepts as length (norm), distance, angles, and orthogonality in non-geometric setups.
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Orthogonal and orthonormal bases, and Gram-Schmidt process in various inner product spaces.
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Symmetric matrices and their properties; orthogonal diagonalization: how it is done and how to understand it geometrically.
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Quadratic forms and their connection to symmetric matrices: uniqueness of this correspondence and its consequences.
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Some concepts from abstract algebra: group, ring, field, and isomorphism; understand the concept of isomorphic vector spaces.
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Note: all the vector spaces discussed in this course are spaces over R (not over the field of complex numbers), and all our matrices have only real entries.
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Solve more advanced problems on eigendecomposition and orthogonality than in the second course.
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Inner product spaces different from R^n: space of continuous functions, spaces of polynomials, spaces of matrices.
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Pythagorean Theorem, Cauchy-Schwarz inequality, and triangle inequality in various inner product spaces.
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Min-max problems using Cauchy-Schwarz inequality, Best Approximation Theorem, least squares solutions.
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Positive/negative definite matrices, indefinite matrices; various methods of determining definiteness of matrices.
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Geometry of quadratic forms in two and three variables: conic sections and quadratic surfaces.
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Crowning of the course and a natural consequence of all the other topics: Singular Value Decomposition and pseudoinverses.
Bklau
Udemy student
The strength of this course is the many solved problems presented in various examples and from different angles.
Additionally a striking balance between theory and practical computations.
Richard B.
Lecturer
This extends Hania's courses one and two with the same title, and it should be the most useful in terms of applications. It also is the hardest to present, if to follow the explicit style of the predecessors. Some abstraction is inevitable, handled carefully enough, but time is mostly spent explaining ideas and examining examples. The lectures are as easy to follow as any lectures could be, perhaps deceptively so, for some ideas are subtle. The students willing to listen and spend some time with the problems will be richly rewarded.
Alp Ö.
Udemy student
Hania Hocamın 1. ve 2. kursunu bitirdim.
Harika bir hoca ve harika bir insan.
İlk iki kurs bana çok şey kattı,
Bu kursun da bana çok şey katacağından eminim.Machine translation: I’ve completed Professor Hania’s first and second courses.
She’s a wonderful teacher and a wonderful person.
The first two courses taught me a lot,
and I’m sure this course will teach me a lot as well.
Andrea T.
Udemy student
This course is exceptional, like the first and second course of this series. The many solved problems deepen the understanding of the very clearly explained theory. Everthing is put into context and into a bigger picture so that with help of this course, you gain understanding of the topic on all levels. Thank you very much Hania for this wonderful experience. I'm awaiting your next courses.
Anonymized User
Udemy student
Good
Adam G.
Udemy student
All of Hania's Linear Algebra courses have been excellent. I completed my engineering education years ago without taking any courses specifically in linear algebra. During that time I learned what I needed to know to solve the problems at hand, which gave me some knowledge but I was lacking in deeper theoretical understanding. These courses have been very interesting for me and gave insight into what all the calculations are actually doing and *why* they are done the way that they are.
Anurag P.
Udemy student
Excellent teaching style, loved the course, must recommend
Tetyana M.
Lecturer
The present is a logical continuation of two earlier courses by Hania, and it is presented in the same spirit – extremely carefully and in detail. It bridges elementary linear algebra with its most standard mathematical applications, motivating the students to further study both. Noteworthy here are applications under the heading of singular value decomposition, basic for what may be called linear data analysis, key to engineering and statistical computations. A warmly recommended course, for prospective data analysts not least.
Alfonso C.
Udemy student
Bien detallado el curso. Aprendí mucho e incluso algunos conceptos que antes no los tenía muy claros.Machine translation: The course was very detailed. I learned a lot, including some concepts that I hadn't quite understood before.
Salvador T.
Udemy student
Excelente presentación y didácticaMachine translation: Excellent presentation and teaching style