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Course overview
Key topics typically include:
- Vectors and vector operations
- Matrices and matrix arithmetic
- Systems of linear equations and methods of solving them
- Determinants and their properties
- Vector spaces, subspaces, and basis
- Eigenvalues and eigenvectors
- Linear transformations and their applications
This course is fundamental for fields like engineering, physics, computer science, data science, and economics, as it provides tools to model and solve real-world problems involving multiple variables and relationships.
What will i learn?
- Here are typical learning outcomes for a Linear Algebra course: Solve systems of linear equations using analytical and matrix-based methods, Perform operations with vectors and matrices, including addition, multiplication, and inversion, Understand and apply concepts of vector spaces, subspaces, basis, and dimension, Compute and interpret determinants, eigenvalues, and eigenvectors 'Analyze and represent linear transformations using matrices ' Apply linear algebra concepts to real-world problems in science, engineering, and computing, Develop logical reasoning and problem-solving skills for abstract mathematical structures.
Requirements
- BSC First Year or BTECH First year
Curriculum for this course
6 Lessons
01:50:37 Hours
Inner Product Space
6 Lessons
01:50:37 Hours
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Inner product space concept, problems and theorems
Preview 00:28:03
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The study of inequalities
Preview 00:23:29
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Orthogonality, Orthonormality and complete orthonormal set
Preview 00:25:31
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Gram schmidt orthogonalization, Bessel's inequality, Parseval's identity
Preview 00:33:14
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Practice MCQ's
Preview .
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Test 1
0:00:20
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