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Elements of Linear Algebra

Constructor University, Fall 2025

Official Class Description from Campusnet

This module is the first in a sequence introducing mathematical methods at the university level in a form relevant for study and research in the quantitative natural sciences, engineering, Computer Science. The emphasis in these modules is on training operational skills and recognizing mathematical structures in a problem context. Mathematical rigor is used where appropriate. However, a full axiomatic treatment of the subject is provided in the first-year modules "Analysis" and "Linear Algebra". The lecture comprises the following topics

News

Contact Information

Instructor: Prof. Sören Petrat
Email: spetrat AT constructor.university
Office: 112, Research I

Teaching Assistants: Flori Kusari, and Anja Tafani.

Time and Place

Lecture/Example/Question sessions (instructor):
Mon, 14:15 - 15:30, ICC East Wing
Tue, 14:15 - 15:30, R.3-51 Lecture Hall (Research III Lecture Hall)

Tutorial, homework help (teaching assistants):
Wed, 12:45 - 14:00, ICC East Wing

How is this class organized?

In each week, you are supposed to:

Textbooks

Table of Contents

Chapter 1: Basic Calculus Review
1.1: Numbers and Polynomials
1.2: Functions

Chapter 2: Vectors and Vector Spaces
2.1: Elementary Analytical Geometry
2.2: Vector Spaces

Chapter 3: Matrices and Linear Equations
3.1: Matrices and Linear Maps
3.2: Systems of Linear Equations
3.3: Matrix Inverse

Chapter 4: Determinants

Chapter 5: Eigenvalues and Eigenvectors
5.1: Eigenvalues/vectors
5.2: Eigenspaces
5.3: Diagonalization

Chapter 6: Special Types of Matrices
6.1: Normal Matrices
6.2: Hermitian/Self-adjoint Matrices
6.3: Real Symmetric Matrices
6.4: Unitary and Orthogonal Matrices

Chapter 7: Matrix Decompositions
7.1: LU Decomposition
7.2: QR Decomposition
7.3: Singular Value Decomposition
7.4: Principal Component Analysis and Best Low-Rank Approximation

Grading

The grade is only based on the final exam. Moodle-quizzes and bi-weekly homework submissions can each provide up to 5% bonus points (i.e., up to 10% bonus points in total can be achieved) according to the following table:

HW percentage solved Bonus percentage
80 or more 5
60 - 79 4
40 - 59 3
20 - 39 2
5 - 19 1
less than 5 0

Exams

There will be one final exam (centrally scheduled in December) and one make-up final exam (centrally scheduled in January).

Links to previous exams will be provided closer to the exam date.

Practice, Practice, Practice

An essential component for doing well in this class is to work on practice exercises. Math is about problem solving (as are almost all sciences)! During this course lots of possibilities for solving exercises are provided on moodle, in the extra example files, and in the tutorial, see below.

Moodle Exercises

Please go to moodle, login, and select the Elements of Linear Algebra class to view the exercises, and the solutions (after the due date). Each week on Monday a new quiz is released, and this is due the following week before the tutorial.

Homework Exercises

These are released bi-weekly, and scans of handwritten solutions are to be uploaded to moodle before the due date.

Extra Material

Class Schedule

Will be updated while class is progressing.

Below, please click on the date to download the lecture notes of this day.

(Note that the book references given below offer only a rough orientation. Sometimes, only parts of a particular chapter are covered in class.)

Note that the videos were recorded for the 2024 version of this class, so they might not contain some minor improvements from the lecture notes.

Date Topics
Week 1 (Sep. 1 - 7, 2025)
Session 1
Notes
Video (2024)
Topic: Review of natural, rational, real, and complex numbers
You will learn about the following topics:
  • Natural numbers, integers, rational numbers, real numbers, complex numbers
  • Polynomials and their roots
  • Irrationality of square root of 2
  • Fundamental Theorem of Algebra
Literature: any Calculus textbook, RHB 1.1
Session 2
Notes
Video (2024)
Topic: Functions, their inverses, and their graphs
You will learn about the following topics:
  • Definition of function, domain and range
  • Discussion of standard functions: absolute value, parabola, hyperbola, sin, cos, tan, exponential function
  • Inverse of a function
Literature: any Calculus textbook
Extra Examples
More on set notation, Complex numbers, Roots of Polynomials, Roots of quadratic equations, Logarithm, Inverse Functions
Extra Material
Sumary of the notation I have used in Week 1 for sets and intervals.
pdf of moodle quiz
Please submit on moodle
pdf of homework sheet

Covering Weeks 1 and 2. Please submit on moodle


Week 2 (Sep. 8 - 14, 2025)
Session 3
Notes
Video
Topic: Vectors in Euclidean space, vector operations, scalar product, cross product
You will learn about the following topics:
  • Vectors and their basic operations
  • Length of a vector
  • Unit vectors
  • Scalar product and its geometrical interpretation
  • Cross product and its geometrical interpretation
Literature: selected topics from RHB Chapter 7
Session 4
Notes
Video
Topic: Lines and planes
You will learn about the following topics:
  • Lines and their parametrizations
  • Lines defined by linear equations
  • Planes and their parametrizations
  • Planes defined by normal vectors
  • Planes defined by linear equations
  • First encounter with systems of linear equations
Literature: RHB 7.7
Extra Examples
Scalar and cross products, Vector application: centroid of a triangle, Lines and planes
pdf of moodle quiz

Please submit on moodle
Week 3 (Sep. 15 - 21, 2025)
Session 5
Notes
Video
Topic: Definition of vector spaces and fields, examples, linear independence basis
You will learn about the following topics:
  • Definition of a vector space
  • Examples and non-examples of vector spaces
  • Definition of a field
  • Examples of fields, e.g., finite fields
  • Concept of linear independence
  • Definition of basis of a vector space
  • Dimension of a vector space
Literature: RHB 8.1, 8.1.1
Session 6
Notes
Video
Topic: Definition and correspondence of linear maps and matrices, basic matrix operations
You will learn about the following topics:
  • Definition of linear maps
  • Linear maps in a chosen basis
  • Definition of a matrix
  • Summary of matrix operations: matrix times vector, matrix times matrix, transpose, Hermitian conjugate
Literature: RHB 8.4, 8.6, 8.7. Strang 2.4
Extra Examples
Basis and linear independence, an example of a linear map
pdf of moodle quiz

Please submit on moodle
pdf of homework sheet

Covering Weeks 3 and 4. Please submit on moodle
Week 4 (Sep. 22 - 28, 2025)
Session 7
Notes
Video
Topic: Homogeneous and inhomogeneous equations, Gaussian elimination
You will learn about the following topics:
  • Geometric intuition for systems of linear equations
  • Relation of the solutions of homogeneous and inhomogenous equations
  • Elementary row operations
  • Augmented matrix notation
  • A first example of Gaussian elimination
Literature: The example in the wikipedia article is good. Strang Ch. 2.2. See also these old class notes of Marcel Oliver about Gaussian Elimination.
Session 8
Notes
Video
Topic: Gaussian elimination, general case
You will learn about the following topics:
  • More examples of Gaussian elimination
  • How to read off the general solution after Gaussian elimination
Literature: same as previous session.
Extra Examples
Two lines in R^2, another exmaple of Gaussian elimination
pdf of moodle quiz

Please submit on moodle
Week 5 (Sep. 29 - Oct. 5, 2025)
Session 9
Notes
Video
Topic: Pivots, kernel, range, rank-nullity theorem
You will learn about the following topics:
  • Reduced row-echelon form
  • Pivots
  • Kernel and nullity, and range/image and rank
  • Rank-nullity theorem
  • Relevance of these concepts for solutions to linear equations
Literature: Strang Ch. 3.2, 3.3, also parts of 3.4, RHB 8.18.1
Session 10
Notes
Video
Topic: Matrix inverse and its computation via Gaussian elimination, basis change
You will learn about the following topics:
  • Inverse of a matrix
  • How to compute the inverse with Gaussian elimination
  • Properties of the inverse
  • Change of basis as application of the matrix inverse
Literature: Strang Ch. 2.5, RHB 8.15 first half
Extra Examples
Matrix inverse, basis change
pdf of moodle quiz

Please submit on moodle
pdf of homework sheet

Covering Weeks 5 and 6. Please submit on moodle
Week 6 (Oct. 6 - 12, 2025)
Session 11
Notes
Video
Topic: Determinant motivation, definition, and properties
You will learn about the following topics:
  • Geometric motivation for considering determinants
  • Definition of the determinant
  • Properties of the determinant
  • Computing a determinant by bringing it into upper triangular form
Literature: Leduc Chapter "The Determinant; Method 2 for defining the determinant". Also Strang Chapter 5 and RHB Chapter 8.9 (the presentation and order of topics is slightly different than in class).
Session 12
Notes
Video
Topic: Determinants: properties, linear independence, Laplace expansion
You will learn about the following topics:
  • Relation between determinant and rank
  • Relation between determinant and linear independence
  • More properties of the determinant
  • Minors, cofactors, and the Laplace expansion
Literature: Leduc Chapter "The Determinant; Method 2 for defining the determinant" and "Laplace Expansions for the Determinant". Also Strang Chapter 5 and RHB Chapter 8.9 (the presentation and order of topics is slightly different than in class).
Extra Examples
Laplace expansion of a 4x4 matrix, Rule of Sarrus, Many Ways to compute a determinant
pdf of moodle quiz

Please submit on moodle
Week 7 (Oct. 13 - 19, 2025)
Session 13
Notes
Video
Summary Video
Topic: Cramer's rule, matrix inverse, Leibniz formula, summaries
You will learn about the following topics:
  • Camer's rule for solving systems of linear equations
  • Computing the matrix inverse using cofactors / the classical adjoint
  • The Leibniz formula to compute determinants
  • Summary: Determinants
  • Summary: Methods to compute determinants
  • Summary: Matrix inverse
  • Summary: A list of equivalences for invertible matrices
Literature: Cramer's rule: in RHB Ch. 8.18.2 "N simultaneous linear equations in N unknowns" there is a small section on Cramer's rule, see also the chapter "Cramer's Rule" in Leduc's book. Invertibility: Leduc, "The classical adjoint of a square matrix", RHB Ch. 8.10 "The inverse of a matrix". Leibniz formula: Leduc "Definitions of the determinant"
Session 14
Notes
Video
Topic: Motivation and definition of eigenvalues and eigenvectors
You will learn about the following topics:
  • Reflection across the diagonal as a motivating example
  • Definition of eigenvalues and eigenvectors
  • Characteristic polynomial and characteristic equation
  • How to compute eigenvalues and eigenvectors
Literature: Leduc: "Definition and Illustration of an Eigenvalue and an Eigenvector", "Determining the Eigenvalues of a Matrix", parts of "Determining the Eigenvectors of a Matrix". RHB: parts of Ch.s 8.13 and 8.14 (the material in that book is organized a bit differently than the lecture notes).
Extra Examples
Cramer's rule, matrix inverse, eigenvalues and eigenvectors of a 3x3 matrix
pdf of moodle quiz

Please submit on moodle
pdf of homework sheet

Covering Weeks 7 and 8. Please submit on moodle
Week 8 (Oct. 20 - 26, 2025)
Session 15
Notes
Video
Topic: Properties of eigenvalues
You will learn about the following topics:
  • Algebraic multiplicity of eigenvalues
  • A formula for the determinant in terms of the eigenvalues
  • A formula for the trace in terms of the eigenvalues
  • Eigenvalues of Hermitian and real symmetric matrices are real
  • Eigenvalues of powers of a matrix
  • Eigenvalues of the matrix inverse
  • Cayley-Hamilton theorem
Literature: Leduc: "Determining the Eigenvectors of a Matrix". Also RHB: parts of Ch.s 8.13 and 8.14 (the material in that book is organized a bit differently than the lecture notes). Strang Ch. 6.1.
Session 16
Notes
Video
Topic: Eigenspaces, and geometric and algebraic multiplicities
You will learn about the following topics:
  • Eigenspaces
  • Geometric multiplicity of eigenvalues
  • A theorem about distinct eigenvalues
Literature: Leduc: parts of "Eigenspaces" and "Diagonalization". Strang: Some parts of Ch. 6.2: "Matrix Powers Ak", and "Nondiagonalizable Matrices (Optional)".
Extra Examples
Properties of eigenvalues and eigenvectors, Google's PageRank part I
pdf of moodle quiz

Please submit on moodle



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