2024/25 Taught Postgraduate Module Catalogue

COMP5710M Algorithms

15 creditsClass Size: 180

Module manager: Dr Sanjukta Roy
Email: S.Roy@leeds.ac.uk

Taught: Semester 1 (Sep to Jan) View Timetable

Year running 2024/25

This module is not approved as an Elective

Module summary

Algorithms and algorithmic problem solving are at the heart of computer science. This module introduces students to the design and analysis of efficient algorithms and data structures. Students learn how to quantify the efficiency of an algorithm and what algorithmic solutions are efficient. Techniques for designing efficient algorithms are taught, include efficient data structures, standard methods such as Divide-and-Conquer and Dynamic Programming as well as more advanced techniques for computationally intractable problems and large data sets. This is done using illustrative and fundamental problems relevant to AI.

Objectives

The aims of this module are to enable students to:

- appreciate and apply algorithmic thinking;

- appreciate what constitutes an efficient and an inefficient solution to a computational problem;

- identify and apply design principles such as greediness, divide and conquer and dynamic programming;

- analyse and implement some fundamental algorithms;

- describe efficient algorithms for fundamental computational problems, along with their computational complexity;

- understand the difference between polynomial and exponential time algorithms;

- know how NP-hard problems can be dealt with in practice;

- appreciate selected cutting-edge modern algorithms;

- articulate the key concepts and justify approaches in a clear and rigorous manner.

Learning outcomes
On completion of the module student should be able to:

1. Demonstrate an understanding of what constitutes an efficient and an inefficient solution to a computational problem;

2. Analyse the efficiency of algorithms;

3. Evaluate and justify appropriate ways to provide efficient solutions for computational problems;

4. Identify and apply design principles such as greediness, divide and conquer and dynamic programming in the design of efficient algorithms;

5. Describe efficient algorithms for a range of computational problems, along with their computational complexity;

6. Articulate the key concepts and critically evaluate approaches in a clear and rigorous manner.

Syllabus

Indicative content for this module includes:

- Algorithmic thinking (the stable matching problem);

- Basic tools: probability, matrices, graphs and networks, mathematical reasoning;

- Time and space complexity, asymptotic analysis of algorithms;

- Algorithms: interval scheduling, median finding, quick-select;

- Algorithm design principles: Greedy algorithms, divide and conquer, dynamic programming; fundamental data structures;

- Intractability: the classes of P and NP;

- Dealing with NP-hard problems in practice;

- Markov chains: computing the page rank;

- Approximation algorithms;

- Modern algorithms: streaming and testing, parametrised algorithms.

Teaching methods

Delivery type	Number	Length hours	Student hours
On-line Learning	6	1.00	6.00
Group learning	6	2.00	12.00
Tutorial	11	1.00	11.00
Private study hours			121.00
Total Contact hours			29.00
Total hours (100hr per 10 credits)			150.00

Private study

Private study will include directed reading and exercises and self-directed research in support of learning activities, as well as in preparation for assessments.

Independent online learning involves non-facilitated directed learning. Students will work through bespoke interactive learning resources and activities in the VLE.

Opportunities for Formative Feedback

Online learning materials will provide regular opportunities for students to check their understanding (for example through formative MCQs with automated feedback). Regular group activity embedded into learning will allow self and peer assessment providing opportunities for formative feedback from peers and tutors.

Methods of assessment

Coursework

Assessment type	Notes	% of formal assessment
In-course Assessment	Report	20.00
In-course Assessment	Report	20.00
Total percentage (Assessment Coursework)		40.00

Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated

Exams

Exam type	Exam duration	% of formal assessment
Standard exam (closed essays, MCQs etc)	2 hr 00 mins	60.00
Total percentage (Assessment Exams)		60.00

The exam will be a computer-based exam. The modules will be reassessed by a computer-based examination.

Reading list

The reading list is available from the Library website

Last updated: 25/09/2024 09:18:38

Disclaimer

Browse Other Catalogues

• Undergraduate module catalogue
• Taught Postgraduate module catalogue
• Undergraduate programme catalogue
• Taught Postgraduate programme catalogue

Errors, omissions, failed links etc should be notified to the Catalogue Team.PROD