COMP30850 Network Analysis

Academic Year 2020/2021

The objective of this module is to provide undergraduate students with a thorough introduction to graph and network analysis from a computer science perspective. The module will cover the basic concepts and key algorithms in network analysis, and discuss their use in the context of many real-world applications across a variety of domains. Students will learn to apply network analysis methods in practice through the medium of the Python programming language.

NOTE: Students taking this module should have previously completed the module COMP30760 "Data Science in Python".

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Curricular information is subject to change

Learning Outcomes:

On completion of this module, students will be able to:
1. Understand the core concepts and algorithms in network analysis.
2. Create appropriate network representations from real-world data.
3. Interpret, compare, and critically appraise different network representations.
4. Competently apply practical methods and tools for network analysis and visualisation.

Indicative Module Content:

The topics covered by this module may include:
- Basic concepts in graphs and networks
- Applications of network analysis
- Representing data as networks
- Network measures and metrics, including centrality
- Path problems and algorithms
- Network visualisation
- Random graph models
- Information diffusion
- Cluster analysis and community finding
- Dynamic networks
- Social media networks

Student Effort Hours: 
Student Effort Type Hours
Lectures

12
Practical

12
Autonomous Student Learning

60
Total

84
Approaches to Teaching and Learning:
Practical Labs; Continuous assessment 
Requirements, Exclusions and Recommendations
Learning Requirements:

Students should have previously successfully completed the module “COMP30760: Data Science in Python - DS”.


Module Requisites and Incompatibles
Not applicable to this module.
 
Assessment Strategy  
Description Timing Open Book Exam Component Scale Must Pass Component % of Final Grade
Class Test: Network theory test Unspecified n/a Graded No

20
Assignment: Assignment 2 Unspecified n/a Graded No

40
Assignment: Assignment 1 Unspecified n/a Graded No

40

Carry forward of passed components
No
 
Resit In Terminal Exam
Summer No
Please see Student Jargon Buster for more information about remediation types and timing. 
Feedback Strategy/Strategies

• Feedback individually to students, post-assessment

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