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This module is discontinued in the selected year. The information shown below is for the academic year that the module was last running in, prior to the year selected.

2015/16 Undergraduate Module Catalogue

COMP2941 Algorithms II

20 creditsClass Size: 85

Module manager: Dr Haiko Muller
Email: H.Muller@leeds.ac.uk

Taught: Semesters 1 & 2 (Sep to Jun) View Timetable

Year running 2015/16

Pre-requisite qualifications

COMP 1740 Mathematics for Computing or equivalent MATH modules

Pre-requisites

COMP1551Core Programming
COMP1641Algorithms I
COMP1740Mathematics for Computing

This module is not approved as a discovery module

Objectives

On completion of this module, students should be able to:
- Understand how to compute with vectors and matrices;
- Appreciate the role of numerical computation in computer science;
- Choose a computational algorithm appropriately, accounting for issues of accuracy, reliabilty and efficiency;
- Understand how to assess/measure the error in a numerical algorithm and be familar with how such errors are controlled;
- Understand the fundamental techniques for the deisgn of efficient algorithms;
- Demonstrate how these algorithms are analysed;
- Understand several advanced data structures, their efficient implementation and applications;
- Understand how these algorithms and data structures relate to the central practical problems of modern computer science.


Skills outcomes
Python


Syllabus

Semester 1:
Vectors and matrices: vectors, vector operations (sum, scalar multiplication, difference, dot product, norm), matrices, matrix operations (sum, scalar multiplication, difference, multiplication), identity matrix; inverse of a matrix.
Approximation: converting a real-world problem, via a mathematical model, to a form which can be understood by a computer; discretising a continuous model; measuring, analysing and controlling approximation errors; balancing accuracy and efficiency. Static systems: simple iterative methods for solving nonlinear scalar equations; direct and iterative methods for solving linear systems of equations.
Evolving systems: differentiation as rate of change and as the limit of a gradient (including derivatives of simple functions); initial value ordinary differential equations, simple methods for initial value problems.
Semester 2:
Principles of algorithm design:
Representations of graphs: adjacency list, adjacency matrix. Depth- and breadth-first search traversals, topological sort, shortest-paths algorithms (Dijkstra's and Floyd's algorithm), minimum spanning tree (Prim's and Kruskal's algorithms, union-find data structure). Algorithmic strategies: greedy algorithm, divide-and-conquer, dynamic programming. Recurrence equations, Master theorem. Strassen's algorithm for matrix multiplication. Hashing, heaps, binary search trees, balanced search trees

Teaching methods

Due to COVID-19, teaching and assessment activities are being kept under review - see module enrolment pages for information

Delivery typeNumberLength hoursStudent hours
Example Class201.0020.00
Class tests, exams and assessment12.002.00
Class tests, exams and assessment13.003.00
Lecture441.0044.00
Private study hours131.00
Total Contact hours69.00
Total hours (100hr per 10 credits)200.00

Private study

- Taught session preparation: 36 hours
- Taught session follow-up: 36 hours
- Self-directed study: 14 hours
- Assessment activities: 45 hours

Opportunities for Formative Feedback

Attendance and summative&formative assessment.

Methods of assessment

Due to COVID-19, teaching and assessment activities are being kept under review - see module enrolment pages for information


Coursework
Assessment typeNotes% of formal assessment
AssignmentPractical Programming Task0.00
AssignmentPractical Programming Task0.00
Problem SheetProblem Sheet 15.00
Problem SheetProblem Sheet 25.00
Problem SheetProblem Sheet 32.50
Problem SheetProblem Sheet 42.50
Problem SheetProblem Sheet 52.50
Problem SheetProblem Sheet 62.50
Total percentage (Assessment Coursework)20.00

This module is re-assessed by exam only.


Exams
Exam typeExam duration% of formal assessment
Standard exam (closed essays, MCQs etc)3 hr 00 mins80.00
Standard exam (closed essays, MCQs etc)2 hr 00 mins0.00
Total percentage (Assessment Exams)80.00

This module is re-assessed by exam only.

Reading list

The reading list is available from the Library website

Last updated: 05/11/2015

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