Module Indicative Content
Further Differentiation: Chain, Product and Quotient Rules and Partial Differentiation applied to polynomials and trig functions.
Probability - Bayes' Theorem. The Normal Distribution.
Introduction to Predicate Calculus - Quantifiers and basic deduction.
2 and 3 Dimensional vectors - Arithmetic, magnitude and scalar product.
Complex Numbers - basic arithmetic in rectangular and polar representations - Argand diagrams.
Algorithmics: Time and Storage complexity - Big O notation - Complexity classes.
Algorithm Paradigms: Divide and Conquer, Greedy Algorithms, Dynamic Programming.
Module Learning Strategies
Two one hour lectures each week.
One one hour tutorial, to reinforce and extend the topics introduced in the lectures.
THIS MODULE WILL NORMALLY RUN IN BOTH SEMESTER 1 AND 2
Module Resources
Students must possess a suitable calculator with trigonometric and logarithmic functions as well as basic statistical functions.
Module Special Admissions Requirements
Prior study of CE61002-1 Mathematics and Statistics for Computing Students and CE00371-1 Introduction to Software Development, or equivalent.
Disqualified Combination - CE61013-1 Maths and Algorithmics
Module Texts
Discrete Mathematics for Computer Scientists, J.Truss - Addison Wesley; ISBN: 0201360616; 1998.
Understanding Algorithms and Data Structures, David Brunskill, John Turner - McGraw-Hill Education - Europe; ISBN: 0077091418; 1996.
Module Additional Assessment Details
1. A suite of multiple choice tests - 50% total, learning outcomes 1-4
2. End Examination - 2 hours - 50% total, learning outcomes 1-4