### Requirements

- This is an introductory course to linear algebra and is designed for students with little or no background in mathematics beyond basic algebra. However, it is helpful if students meet the following requirements :
- High school mathematics: Students should have a good understanding of high school mathematics, including algebra, geometry, and trigonometry. These subjects form the foundation for linear algebra and are necessary for understanding the concepts and techniques.
- College-level mathematics: In some cases, students may need to have completed a college-level mathematics course, such as calculus, before taking an introductory course in linear algebra. This is because some topics in linear algebra, such as determinants and eigenvalues, require calculus knowledge.
- Readiness to learn abstract concepts: Linear algebra involves learning abstract concepts and theoretical proofs. Students should be prepared to think abstractly and understand mathematical notation.
- Time commitment: Linear algebra is a challenging subject that requires time and effort to master. Students should be prepared to devote sufficient time to studying, practicing, and solving problems.
- Trigonometry: Students should have a basic understanding of trigonometry, including the definitions of sine, cosine, and tangent.
- Proficiency in proof techniques: Linear algebra involves proofs of various theorems and properties, so it's important to have a good understanding of proof techniques such as direct proof, proof by contradiction, and proof by induction.

### Features

- This introductory course in linear algebra typically includes the following features:
- Fundamentals of linear algebra: The course covers the basic concepts of linear algebra, such as systems of linear equations, matrices, vectors, vector spaces, linear transformations, and eigenvalues and eigenvectors.
- Lectures: The course includes lectures, online, where students can learn on their own the concepts and techniques of linear algebra and provides examples to help students understand the material.
- Homework: Students are typically assigned homework problems to reinforce the concepts learned in class and help them practice problem-solving skills.
- Quizzes and exams: The course includes quizzes and exams to assess students' understanding of the material and to provide feedback on their progress.
- Office hours: The instructor typically holds office hours, either in-person or online, to provide additional support to students who need extra help.
- Applications: The course may include applications of linear algebra in diverse fields, such as computer science, physics, engineering, and economics, to help students understand the real-world relevance of the concepts they are learning.
- Online resources: The course may provide online resources such as video lectures, discussion forums, and interactive simulations to enhance students' understanding of the material.

### Target audiences

- The target audience for an introductory course in linear algebra typically includes undergraduate students in fields such as mathematics, engineering, physics, economics, computer science, and other related fields. The course is also suitable for individuals interested in learning the fundamentals of linear algebra for personal or professional development.
- Students in economics, finance, and social sciences who need to understand matrix operations and systems of linear equations to model real-world problems.
- Anyone interested in machine learning and data science, as linear algebra is a foundational concept in these fields.
- High school students who are interested in mathematics and want to get a head start on college-level coursework.
- Professionals in fields such as data science, machine learning, and optimization who use linear algebra as a tool in their work.
- Anyone with an interest in mathematics who wants to learn about the fundamental concepts of linear algebra.
- Graduate students in the above fields who may have a limited background in linear algebra and need to review or strengthen their knowledge.
- The course assumes a basic understanding of algebra and calculus, so students should have completed courses in those subjects prior to enrolling. Some familiarity with vectors, matrices, and systems of linear equations is also helpful, but not required.
- Professionals in fields such as engineering, physics, or computer science who need to refresh their understanding of linear algebra: Even if someone has taken a linear algebra course in the past, they may benefit from a refresher course to brush up on the basics and stay up-to-date with new developments in the field.

Linear algebra is a branch of mathematics that deals with the study of vectors, matrices, and linear transformations. It provides a framework for solving various problems in science, engineering, and other fields. Given a system of linear equations, there is a corresponding matrix called an “augmented matrix.” On a matrix, we can perform three types of operations:

- Exchange two rows,
- multiply an entire row by a nonzero scalar, and
- add a multiple of one row to another.

A matrix can be reduced to a matrix called row echelon form or reduced row echelon form. To any linear system, there is a corresponding matrix called an “augmented matrix” and vice versa. Solving a linear system corresponding to an augmented matrix is equivalent to solving the linear system associated with its row echelon form or reduced row echelon form.

Linear algebra can be used to solve systems of linear equations, which arise in many areas of science and engineering. It is also used in data analysis and machine learning, where it is used to find patterns and relationships in large datasets.

The basic objects in linear algebra are vectors and matrices. A vector is a quantity with both magnitude and direction, such as the force applied to an object or the velocity of a moving object. A matrix is a rectangular array of numbers representing linear transformations and systems of linear equations.

Linear algebra also includes the study of linear transformations, which are functions that preserve the structure of vectors and matrices. These transformations can be used to represent rotations, reflections, and other types of geometric operations.

In addition to its applications in science and engineering, linear algebra has many theoretical applications. It is used in the study of abstract algebra, functional analysis, and other areas of mathematics.

This course is typically an introductory-level course that covers the fundamental concepts of linear algebra, including vectors, matrices, linear transformations, and systems of linear equations. The course aims to provide students with a solid understanding of linear algebraic concepts and their applications in various fields.

The following are some topics that will be covered in this course:

- Systems of linear equations: The concept of linear systems of equations, methods for solving linear systems of equations, including row reduction, Gaussian and Gauss-Jordan elimination, matrix inversion, and Cramer’s rule.
- Matrices: The definition and properties of matrices, matrix operations, matrix algebra, and matrix multiplication.
- Determinants: The concept of determinants, properties of determinants, and how they can be used to compute the inverse of a matrix.
- Vectors and vector spaces: The concept of vectors, vector operations, and vector spaces, including linear independence, basis, and dimension.
- Linear transformations: The definition and properties of linear transformations, including the concept of kernel and image and how they can be represented using matrices.
- Eigenvalues and eigenvectors: The definition and properties of eigenvalues and eigenvectors and how they can be used to diagonalize a matrix and solve problems related to linear transformations.

By the end of the course, students should have a solid understanding of linear algebraic concepts and their applications and be able to apply this knowledge to solve problems in various fields.

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