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MA1006: ALGEBRA (2024-2025)

Last modified: 12 Sep 2024 10:46


Course Overview

This course introduces the concepts of complex numbers, matrices and other basic notions of linear algebra over the real and complex numbers. This provides the necessary mathematical background for further study in mathematics, physics, computing science, chemistry and engineering.




Course Details

Study Type Undergraduate Level 1
Term First Term Credit Points 15 credits (7.5 ECTS credits)
Campus Aberdeen Sustained Study No
Co-ordinators
  • Dr Simona Paoli

Qualification Prerequisites

  • Either Programme Level 1 or Programme Level 2

What courses & programmes must have been taken before this course?

  • Any Undergraduate Programme
  • One of Mathematics (MA) or Physics (PX) or Bachelor Of Science In Geophysics or Bachelor Of Science In Data Science or Master of Engineering in Computing Science or Master Of Engineering In Computing Science (Cybersecurity) or Higher Grade (Sce/Sqa) Mathematics at Grade A1/A2/A/B3/B4/B/C5/C6/C
  • Either Programme Level 1 or Programme Level 2

What other courses must be taken with this course?

None.

What courses cannot be taken with this course?

Are there a limited number of places available?

No

Course Description

The basic course includes a discussion of the following topics: complex numbers and the theory of polynomial equations, vector algebra in two and three dimensions, systems of linear equations and their solution, matrices and determinants.

Syllabus

  • Solving equations.
  • Polynomial equations and their roots, polynomial long division, the Rational root theorem.
  • Introduction to complex numbers. The addition, subtraction, multiplication and division of
  • Complex numbers. Modulus and Argument and the representation of such numbers on an Argand diagram. Loci and regions in the Argand diagram. De Moivre’s theorem and applications. Complex exponential, logarithm, sine and cosine.
  • Systems of linear equations, Gaussian elimination.
  • Matrix algebra. Determinants of square matrices (of any dimension). Matrix inversion (the cofactor method and Gaussian elimination).
  • Vectors and linear maps. Special matrices (e.g rotation matrices). Matrix design. Eigenvalues and eigenvectors.
  • Topics from: Diagonalizability. Subspaces, dimensions and linear independence. The rank and nullity of a matrix.

Contact Teaching Time

Information on contact teaching time is available from the course guide.

Teaching Breakdown

More Information about Week Numbers


Details, including assessments, may be subject to change until 30 August 2024 for 1st term courses and 20 December 2024 for 2nd term courses.

Summative Assessments

Class Test

Assessment Type Summative Weighting 15
Assessment Weeks Feedback Weeks

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Learning Outcomes
Knowledge LevelThinking SkillOutcome
Sorry, we don't have this information available just now. Please check the course guide on MyAberdeen or with the Course Coordinator

Exam

Assessment Type Summative Weighting 70
Assessment Weeks Feedback Weeks

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Learning Outcomes
Knowledge LevelThinking SkillOutcome
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Class Test

Assessment Type Summative Weighting 15
Assessment Weeks Feedback Weeks

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Learning Outcomes
Knowledge LevelThinking SkillOutcome
Sorry, we don't have this information available just now. Please check the course guide on MyAberdeen or with the Course Coordinator

Formative Assessment

There are no assessments for this course.

Resit Assessments

Best of written exam (100%) or written exam (70%) with carried forward in-course assessment (30%)

Assessment Type Summative Weighting
Assessment Weeks Feedback Weeks

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Learning Outcomes
Knowledge LevelThinking SkillOutcome
Sorry, we don't have this information available just now. Please check the course guide on MyAberdeen or with the Course Coordinator

Course Learning Outcomes

Knowledge LevelThinking SkillOutcome
ConceptualRememberKnow the definition of complex numbers and their essential role in mathematics
ProceduralApplyCarry out division of polynomials and solve polynomial equations up to degree three.
ProceduralApplyPerform calculations, such as matrix inversion, finding eigenvalues and eigenvectors, and diagonalization.
FactualUnderstandHave an understanding of the need of precision in mathematics
ConceptualUnderstandUnderstand matrix representation of systems of linear equations.
ConceptualApplyHave a working knowledge of basic logical rules
ProceduralApplySolve systems of linear equations using Gaussian elimination.
ProceduralApplyPerform elementary manipulation of complex numbers and their geometrical representation.

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