Linear Maps (Transformations) - Linear Algebra (Undergraduate Advanced)

A comprehensive study of linear transformations (or maps) - definition, kernel, range, matrix representation and related matters.

23 hrs

Enrolment valid for 12 months
This course is also part of the following learning tracks. You may join a track to gain comprehensive knowledge across related courses.
MTH 202: Mathematical Methods II
MTH 202: Mathematical Methods II
Comprehensive treatise of advanced mathematics covering vector calculus, complex numbers, linear vector spaces, linear maps, matrices, eigenvalues and eigenvectors. Curated for second-year students of engineering and physical sciences at Obafemi Awolowo University, Ile-Ife, Nigeria. Students and professionals with similar learning goal will also find this learning track useful.

Comprehensive treatise of advanced mathematics covering vector calculus, complex numbers, linear vector spaces, linear maps, matrices, eigenvalues and eigenvectors. Curated for second-year students of engineering and physical sciences at Obafemi Awolowo University, Ile-Ife, Nigeria. Students and professionals with similar learning goal will also find this learning track useful.

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MTH 204: Linear Algebra I
MTH 204: Linear Algebra I
Master the algebraic structures that underpin modern science and computation. This academic track delivers the complete NUC CCMAS MTH 204 curriculum, moving rigorously from abstract vector spaces to practical matrix theory. It provides the essential mathematical toolkit required for advanced problem-solving in high-demand STEM fields. This programme is targeted at undergraduates in mathematics, engineering, and computer science requiring a firm grounding in linear structures. It also serves professionals in data science, cryptography, and machine learning needing a rigorous theoretical refresher on foundational concepts. You will achieve competence in manipulating abstract vector spaces, determining basis and dimension, and analyzing linear transformations through their kernels and images. You will master matrix arithmetic, compute determinants, solve systems of linear equations using advanced methods, and apply techniques of eigenvalues and diagonalization. Completion establishes the critical foundation demanded for advanced studies in multivariate calculus, differential equations, and complex computational algorithms.

Master the algebraic structures that underpin modern science and computation. This academic track delivers the complete NUC CCMAS MTH 204 curriculum, moving rigorously from abstract vector spaces to practical matrix theory. It provides the essential mathematical toolkit required for advanced problem-solving in high-demand STEM fields. This programme is targeted at undergraduates in mathematics, engineering, and computer science requiring a firm grounding in linear structures. It also serves professionals in data science, cryptography, and machine learning needing a rigorous theoretical refresher on foundational concepts. You will achieve competence in manipulating abstract vector spaces, determining basis and dimension, and analyzing linear transformations through their kernels and images. You will master matrix arithmetic, compute determinants, solve systems of linear equations using advanced methods, and apply techniques of eigenvalues and diagonalization. Completion establishes the critical foundation demanded for advanced studies in multivariate calculus, differential equations, and complex computational algorithms.

See more

Course Chapters

1. Introduction
5
Welcome and course outline. Review of elementary matrix and linear vector space concepts.
Concept Overviews
5 Lessons
1:39:29
2. Maps
6
Definition of a map (also mapping or transformation) between two sets, notations and some general properties of maps.
Concept Overviews
6 Lessons
1:56:05
3. Linear Maps
3
15
Definition, examples and general properties of linear maps.
Concept Overviews
3 Lessons
1:07:34
Problem Walkthroughs
15 Lessons
3:03:53
4. Algebra of Linear Maps
5
2
Analysis of the vector space of all linear maps between two given vector spaces. Addition, scalar multiplication, composition and inverse of linear maps.
Concept Overviews
5 Lessons
2:12:07
Problem Walkthroughs
2 Lessons
21:59
5. Operations on Linear Maps
1
3
Further operations on linear maps involving their definition and properties.
Concept Overviews
1 Lesson
7:04
Problem Walkthroughs
3 Lessons
1:00:46
6. Kernel
1
3
Meaning of the kernel of a linear map, with worked examples.
Concept Overviews
1 Lesson
23:28
Problem Walkthroughs
3 Lessons
53:00
7. Range
1
3
Meaning of the range of a linear map, with worked examples.
Concept Overviews
1 Lesson
24:54
Problem Walkthroughs
3 Lessons
1:11:45
8. Matrix Representation
3
3
Matrix representation of a linear map, with worked examples.
Concept Overviews
3 Lessons
1:17:50
Problem Walkthroughs
3 Lessons
59:06
9. Transition Matrix
4
2
Meaning and properties of the transition matrix between two bases of a vector space.
Concept Overviews
4 Lessons
1:25:14
Problem Walkthroughs
2 Lessons
57:00