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COMP52215: Advanced Algorithms and Discrete Systems

It is possible that changes to modules or programmes might need to be made during the academic year, in response to the impact of Covid-19 and/or any further changes in public health advice.

Type Tied
Level 5
Credits 15
Availability Available in 2023/24
Module Cap None.
Location Durham
Department Computer Science

Prerequisites

  • PHYS52015 Introduction to Scientific and High Performance Computing

Corequisites

  • n/a

Excluded Combinations of Modules

  • n/a

Aims

  • Provide advanced knowledge and critical understanding of paradigms, fundamental ideas, algorithms and methods behind the modelling and simulation of discrete systems
  • Provide advanced knowledge and critical understanding of paradigms, fundamental ideas and methods behind advanced algorithms

Content

  • Advanced Algorithms
  • Discrete Systems

Learning Outcomes

Subject-specific Knowledge:

  • Understanding and critical reflection of advanced ideas, numerical techniques and algorithms used to study discrete models
  • Understanding and critical reflection of advanced engineering algorithms in high-performance computing and data analysis

Subject-specific Skills:

  • Basic familiarity with state-of-the-art algorithms to solve large-scale and data intense challenges
  • Competence to translate discrete problem descriptions into algorithmic formulations; competent and educated selection of appropriate solution algorithms

Key Skills:

  • Familiarity with advanced paradigms and modern algorithms underlying scientific computing for discrete systems, and their analysis

Modes of Teaching, Learning and Assessment and how these contribute to the learning outcomes of the module

  • Teaching will be by lectures and workshops.
  • The lectures provide the means to give a concise, focused presentation of the subject matter of the module.
  • When appropriate, the lectures will also be supported by the distribution of written material, or by information and relevant links on Ultra.
  • Regular problem exercises and workshops will give students the chance to develop their theoretical understanding and problem solving skills.
  • Students will be able to obtain further help in their studies by approaching their lecturers, either after lectures or at other mutually convenient times.
  • Student performance will be summatively assessed through coursework.
  • The formative coursework provides opportunities for feedback, for students to gauge their progress and for staff to monitor progress throughout the duration of the module.

Teaching Methods and Learning Hours

ActivityNumberFrequencyDurationTotalMonitored
Lectures for Advanced Algorithms123 per week60 minutes12 
Practical Classes for Advanced Algorithms41 per week60 minutes4 
Lectures for Discrete Systems123 per week60 minutes12 
Practical Classes for Discrete Systems41 per week60 minutes4 
Self Study118 
Total150 

Summative Assessment

Component: Summative CourseworkComponent Weighting: 100%
ElementLength / DurationElement WeightingResit Opportunity
Advanced Algorithms Coursework1 week50Yes
Discrete Systems Coursework1 week50Yes

Formative Assessment

n/a

More information

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