The module will build on software engineering skills into the area of managing large data sets for processing and analysis.

Areas that may be addressed...

The module will build on software engineering skills into the area of managing large data sets for processing and analysis.

Areas that may be addressed include:

Scaling principles including horizontal and vertical scaling

Distributed Computing including scalability, reliability and achieving consensus

Map Reduce processing

Streaming architectures

Data Pipelines

DataOps

Large scale data storage strategies

Distributed Architectures Centralised and decentralised distributed architectures

Data Flows including: Message Queues Web Services

Networks are a universal way to model and analyse complex social, technological, and business systems and their interactions both in space and time.  This...

Networks are a universal way to model and analyse complex social, technological, and business systems and their interactions both in space and time.  This course aims to introduce students to the fundamentals of network analysis, complex networks and their structure and function, with ways to understand the patterns and interdependencies that are agnostic to the study domain. Topics include notions of centrality, influence and authority, graph communities, knowledge graphs, and dynamic networks.

Important business decisions cannot be left to intuition alone. We need to communicate the structure of our reasoning, defend it to adversarial challenges and...

Important business decisions cannot be left to intuition alone. We need to communicate the structure of our reasoning, defend it to adversarial challenges and make presentations that show we have done a thorough analysis. We also need to make sense out of various sources of data, organise the inputs of experts and colleagues, and use state-of-the-art tools to provide analytical support for our reasoning.

The objective of this course is to equip you to be more effective in these tasks. You will develop skills in data analysis, structuring decisions, building decision models, risk assessment, decision making under uncertainty, recognising areas where business analysis can add value, selecting appropriate types of analyses and learn to apply them in a small scale, quick-turnaround fashion.

The aims of this module are:

To provide students with an understanding of how to structure business decisions, build decision models and assess risk.

To introduce students to the challenges of decision-making under uncertainty and to help them understand where structured approaches to decision and risk analysis can add value.

To provide students with practical experience of working with state-of-the-art decision support software.