Linear Algebra Course Information, Lecture notes of Algebra

Information about the Linear Algebra course, which is an introductory course on linear algebra, one of the most important and basic areas of mathematics, with many real-life applications. The course introduces students to both the theory of vector spaces and linear transformations and the techniques such as row-reduction of matrices and diagonalisation, which can be applied to problems in areas such as engineering, economics, and mathematical biology. The document also provides information about the course requirements, grading of assignments, and course materials.

Typology: Lecture notes

2021/2022

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MATH-UA-140
Linear Algebra
Instructor Information
TBD
Course Information
Normal prerequisite: Calculus 1 with a C or higher (or equivalent)
Course Overview and Goals
This is an introductory course on linear algebra, one of the most important and basic
areas of mathematics, with many real-life applications. The course introduces students to
both the theory of vector spaces and linear transformations and the techniques such as
row-reduction of matrices and diagonalisation, which can be applied to problems in areas
such as engineering, economics, and mathematical biology.
As well as mastering techniques, it is important that the students get to grips with the
more abstract ideas of linear algebra, and learn to understand and write correct
mathematical arguments. Taking an active approach to problem-solving is also important.
The class will consist of a mixture of lectures, working on problems and class discussions.
Each class will correspond to two or three sections of the recommended text, which
students will be expected to read. There will be weekly assignments, which are a very
important part of the learning process: actively engaging with the mathematics is crucial.
Upon Completion of this Course, students will be able to:
Understand the basic theory of vector spaces: linear independence, spanning,
bases, dimension, subspaces.
Understand the basic theory of linear transformations: matrix representation,
diagonalisation, orthogonal diagonalisation
Carry out the basic techniques of the following: row-reduction and LU
decomposition to solve systems of linear equations; calculating determinants;
finding eigenvalues and eigenvectors and diagonalising matrices; orthogonally
diagonalising matrices.
Apply linear algebra to solve some real-life problems.
Be able to work with formal mathematical arguments.
Course Requirements
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MATH-UA- 140

Linear Algebra

Instructor Information

 TBD

Course Information

● Normal prerequisite: Calculus 1 with a C or higher (or equivalent)

Course Overview and Goals

This is an introductory course on linear algebra, one of the most important and basic areas of mathematics, with many real-life applications. The course introduces students to both the theory of vector spaces and linear transformations and the techniques such as row-reduction of matrices and diagonalisation, which can be applied to problems in areas such as engineering, economics, and mathematical biology. As well as mastering techniques, it is important that the students get to grips with the more abstract ideas of linear algebra, and learn to understand and write correct mathematical arguments. Taking an active approach to problem-solving is also important. The class will consist of a mixture of lectures, working on problems and class discussions. Each class will correspond to two or three sections of the recommended text, which students will be expected to read. There will be weekly assignments, which are a very important part of the learning process: actively engaging with the mathematics is crucial.

Upon Completion of this Course, students will be able to:

● Understand the basic theory of vector spaces: linear independence, spanning, bases, dimension, subspaces. ● Understand the basic theory of linear transformations: matrix representation, diagonalisation, orthogonal diagonalisation ● Carry out the basic techniques of the following: row-reduction and LU decomposition to solve systems of linear equations; calculating determinants; finding eigenvalues and eigenvectors and diagonalising matrices; orthogonally diagonalising matrices. ● Apply linear algebra to solve some real-life problems. ● Be able to work with formal mathematical arguments.

Course Requirements

Grading of Assignments

The grade for this course will be determined according to these assessment components: Assignments/ Activities Description of Assignment % of Final Grade Due Homework Weekly homework, given out at one class and handed in at the class a week later 30% At each class Mid-term 1 Test on material from Chapters 1 – 3 ( 75 minutes) 15 % Oct 16 Mid-term 2 Test on material from Chapters 4 – 5 ( 75 minutes) 15 % Nov 12 Final exam Exam on all material (from Chapters 1 – 7) (2 hours) 40% Dec 11 Failure to submit or fulfill any required course component results in failure of the class Grades Letter grades for the entire course will be assigned as follows: Letter Grade Percent Description A/A- 90 - 100 % Good understanding of ideas: ability to carry out calculations accurately: ability to produce and understand proofs and solve unseen conceptual problems. B-/B/B+ 80 - 89 % Reasonable understanding of ideas: ability to carry our calculations accurately: some ability to produce proofs. C-/C/C+ 70 - 79% Reasonable understanding of ideas: ability to carry our calculations fairly accurately. D/D+ 65 – 69% Some basic understanding of ideas and ability to carry our calculations with some degree of success F 0 – 64% Ideas not understood and inability to do calculations Course Materials

Required Textbooks & Materials

● Linear Algebra and its applications (4th or 5th^ edition) by David Lay

Optional Textbooks & Materials

● You may like to look at other Linear Algebra text-books, e.g. by Strang. However, we will follow the notation and presentation of material used in the text by Lay.

Session/Date Topic Reading

Assignment

Due

5.2 The characteristic equation 5.3 Diagonalisation Session 11 : Nov 13 5.4 Eigenvectors and linear transformations 6.1 Inner products 6.2 Orthogonal sets Section 5.4, 6.1, 6.2 n/a Session 12 : Nov 20 Mid-term 2 (on Chapters 4 – 5) 6.3 Orthogonal projections Section 6.3 CW 9: Nov 27 Session 13 : Nov 27 6.4 Gram-Schmidt process 6.5 Least squares problem 7.1 Diagonalization of symmetric matrices Sections 6.4, 6.5, 7.1 CW 10: Dec 3 Session 14 : Dec 3 7.2 Quadratic forms Catch-up/Revision Section 7.2 n/a Final Assessment: Dec 10 Final test (on all material covered) n/a n/a Co-Curricular Activities n/a Classroom Etiquette  Mobiles off during class, please. Academic Policies

Attendance and Tardiness

 TBD

Assignments, Plagiarism, and Late Work

 You can find details on these topics and more on the Policies and Procedures section of the NYU website for students studying away at global sites (https://www.nyu.edu/academics/studying-abroad/upperclassmen-semester- academic-year-study-away/academic-resources/policies-and-procedures.html).

Classroom Conduct

Academic communities exist to facilitate the process of acquiring and exchanging knowledge and understanding, to enhance the personal and intellectual development of its members, and to advance the interests of society. Essential to this mission is that all members of the University Community are safe and free to engage in a civil process of teaching and learning through their experiences both inside and outside the classroom. Accordingly, no student should engage in any form of behaviour that interferes with the

academic or educational process, compromises the personal safety or well-being of another, or disrupts the administration of University programs or services. Please refer to the NYU Disruptive Student Behavior Policy for examples of disruptive behavior and guidelines for response and enforcement.

Disability Disclosure Statement

Academic accommodations are available for students with disabilities. Please contact the Moses Center for Students with Disabilities (212- 998 - 4980 or [email protected]) for further information. Students who are requesting academic accommodations are advised to reach out to the Moses Center as early as possible in the semester for assistance. Instructor Bio