Singapore University of Social Sciences

Linear Algebra (MTH207)

Applications Open: 01 April 2019

Applications Close: 31 May 2019

Next Available Intake: July 2019

Course Types: Modular Undergraduate Course

Language: English

Duration: 6 months

Fees: $1312 View More Details on Fees

Area of Interest: Science & Technology

Schemes: Lifelong Learning Credit (L2C)

Funding: To be confirmed


MTH207 introduces essentials of linear algebra and shows the relationships between them. As linear algebra uses linear transformations to study systems of linear equations, students should have a sound knowledge of mathematics, as developed in Further Discrete Mathematics and Further Calculus and Algebra.

Level: 2
Credit Units: 5
Presentation Pattern: Every July
E-Learning: BLENDED - Learning is done MAINLY online using interactive study materials in Canvas. Students receive guidance and support from online instructors via discussion forums and emails. This is supplemented with SOME face-to-face sessions. If the course has an exam component, this will be administered on-campus.


  • Evaluate determinants by row or column expansions.
  • List and use properties of determinants.
  • Define systems of linear equations and the nature of their solutions.
  • Solve linear systems by Gaussian Elimination and Gauss-Jordon methods.
  • Define and list properties of Linear Transformations.
  • Perform matrix algebra.
  • Define general vector space V.
  • Define basis and dimension of V.
  • Find row space, Column space and Null space of an m x n matrix.
  • Find rank and nullity of a matrix.
  • Orthogonality.
  • Eigenvalues and Eigenvectors.

Learning Outcome

  • Show how to prove a mathematical statement in linear algebra.
  • Calculate the determinant, eigenvalues and/or eigenvectors of a square matrix.
  • Determine whether given subsets are linearly independent or are spanning sets of given subspaces.
  • Compute row echelon form, row space, column space, null space or rank of a given matrix.
  • Apply the Gram-Schmidt process to obtain an orthonormal basis for a given inner product space.
  • Solve system of linear equations.
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