Module 18189.2 (2004)

Syllabus page 2004/2005

06-18189
Mathematics for Computer Science

Level 1/C

Unknown/Left
Achim Jung
Achim Jung (coordinator)
10+10 credits in Semester 1 and Semester 2

Links | Outline | Aims | Outcomes | Prerequisites | Teaching | Assessment | Books | Detailed Syllabus


The Module Description is a strict subset of this Syllabus Page. (The University module description has not yet been checked against the School's.)

Changes and updates

New module for 2004/05 (in part replaces Maths and Logic A & B). Examination length increased to 3 hrs after discussion with students.


Relevant Links


Outline

The module provides an introduction to mathematical concepts relevant to computer science. Discrete mathematics: numbers and arithmetic; elementary set theory, relations and functions; proofs and mathematical induction; elementary counting principles; binomial theorem; graphs and trees. Linear algebra: concepts, structures and methods, placing special emphasis on their application in modelling and solving computational problems.


Aims

The aims of this module are to:

  • introduce the basic discrete mathematics concepts that have applications in computer science
  • introduce the core concepts and fundamental algorithms of linear algebra
  • illustrate how linear algebra concepts and algorithms help in solving computational problems

Learning Outcomes

On successful completion of this module, the student should be able to: Assessed by:
1 apply basic set theory Continuous assessment, examination
2 apply the concept of equivalence relations and theorems about them Continuous assessment, examination
3 apply the principle of mathematical induction Continuous assessment, examination
4 perform combinatorial enumeration and use binomial coefficients and factorial notation Continuous assessment, examination
5 apply the concept of a combinatorial graph and tree Continuous assessment, examination
6 apply linear algebra algorithms on paper to small problem instances Continuous assessment, examination
7 explain how these algorithms can be implemented, recognizing numerical stability issues Continuous assessment, examination
8 identify and explain the structural and conceptual elements of linear algebra in computational settings Continuous assessment, examination
9 apply linear algebra as a modelling language and as a solution technique for computational problems Continuous assessment, examination

Restrictions, Prerequisites and Corequisites

Restrictions:

None

Prerequisites:

None

Co-requisites:

None


Teaching

Teaching Methods:

2 hrs lectures, 1 hr tutorial/exercise class per week

Contact Hours:

70


Assessment

  • Supplementary (where allowed): As the sessional assessment
  • 3 hr examination (80%), continuous assessment (20%). Resit by examination only with the continuous assessment mark carried forward.

Recommended Books

TitleAuthor(s)Publisher, Date
Discrete MathematicsS. Lipschuts & M. LipsonSchaum Outline Series,

Detailed Syllabus

  1. Sets (~5 hours)
    • Set notation - including standard sets N, Z, Q, R
    • Equality of sets (with proofs)
    • Predicate notation: { x : P(x) }
    • Subsets; union, intersection, difference, complement; algebra of sets
    • Distributive laws; de Morgan laws
    • Ordered pairs and triples; cartesian products
    • Power set
  2. Sets and logic (throughout)
  3. Relations and functions (4-5 hours)
    • Partitions and equivalence relations
    • Partial order relations
    • Functions; one-one, onto, bijections
  4. Proofs (~3 hours and throughout)
    • Sequences, recurrences and induction
  5. Counting (4-5 hours)
    • Sum rule; inclusion-exclusion
    • Product rule
    • Binomial coefficients and binomial theorem (positive integer exponent)
  6. Graphs and trees (~3 hours)
    • Handshaking lemma; degree sequences
    • Specific families: complete graphs, circuits, paths, complete bipartite
    • Connectedness; bipartiteness
    • Trees, rooted trees; links with partial orders
  7. Numbers and arithmetic (~3 hours)
    • What are real numbers and how are they represented?
    • Fractions and decimals
    • Rationals and irrationals
    • Elementary algebra (revision)
  8. Number systems
    • Review of natural numbers, integers, rationals, and the reals
    • Computing modulo a number
    • Complex numbers
  9. Systems of linear equations
    • Gaussian elimination
    • Underspecified equation systems
    • Overspecified equation systems
  10. Analytic geometry
    • Representing lines and planes, intersection
    • Orthogonality and projection
    • Bases in the plane and in three-dimensional space
  11. Linear transformations and matrices
    • Types of linear transformations
    • Description of linear transformations with matrices
    • Matrix algebra
    • Base changes
  12. Vector spaces
    • General definition and examples
    • Linear and affine subspaces
    • Orthogonalisation
  13. Determinants
    • Determinants
    • Eigenvalues and eigenvectors
    • Diagonalisation

Last updated: 8 Apr 2005

Source file: /internal/modules/COMSCI/2004/xml/18189.xml

Links | Outline | Aims | Outcomes | Prerequisites | Teaching | Assessment | Books | Detailed Syllabus