Module Descriptors
MATHEMATICS AND ALGORITHMICS
XXAT50338
Key Facts
Faculty of Computing, Engineering and Sciences
Level 5
15 credits
Hours of Study
Scheduled Learning and Teaching Activities: 36
Independent Study Hours: 114
Total Learning Hours: 150
Assessment
- CLASS-TEST weighted at 50%
- EXAMINATION - UNSEEN IN EXAMINATION CONDITIONS weighted at 50%
Module Details
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
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.
Understanding Algorithms and Data Structures, David Brunskill, John Turner - McGraw-Hill Education - Europe; ISBN: 0077091418; 1996.
Module Special Admissions Requirements
Prior study of CE61002-1 Mathematics and Statistics for Computing Students, or equivalent.
Module Resources
Students must possess a suitable calculator with trigonometric and logarithmic functions as well as basic statistical functions.
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
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 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.
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.