Postgraduate Certificate in Big Data Analytics

Structure

The online PGCert in Big Data Analytics has four core modules. The first module takes 10 weeks, each subsequent module lasts eight weeks.

  • The Global Technology Environment
  • Big Data
  • Data Mining
  • Data Visualisation and Warehousing

Core modules

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The Global Technology Environment (10 weeks)

Objective
To lay the foundation for successful study, and provide students with a comprehensive understanding of the key concepts associated with the computing environment.

Description
Start your personal and professional journey with this on-boarding module for the MSc in Cyber Security programme, where you will be introduced to the online learning environment. The module provides a critical "state-of the-art" review of the domain of information technology (IT). It is designed to offer a wide-ranging understanding on topics such as software engineering, cyber security and big data analytics.

By completing the module, you will have a comprehensive global view of the current IT landscape in the context of both commercial and non-commercial enterprises. The module blends both theory and practice, so that a solid foundation is provided for future study.

Curriculum insights

  • Key concepts in the IT industry
  • Enterprise-oriented software and systems enterprise development
  • Data management and big data analytics
  • Cyber security and risk management
  • Current and emerging IT trends
  • Global characteristics of IT

Big Data (8 weeks)

Objective
To provide students with a comprehensive understanding of big data tools and techniques, related issues, and the different kinds of big data ecosystems that can be used to support advanced data analytics.

Description
This module will consider big data management frameworks in general, but with a focus on the Hadoop open-source data storage and processing platform and its underpinning sub-systems. It also provides you with a critical awareness of how big data systems support data-driven decision making.

Curriculum insights

  • Key concepts and technologies in big data
  • Hadoop
  • Practical solutions to big data problems
  • Integration and deployment of big data

Data Mining (8 weeks)

Objective
To provide students with a detailed understanding of the concepts of data mining, including the processes involved and the tools and techniques commonly used.

Description
During this module, you will be provided the opportunity to apply the tools and techniques of data mining to a variety of example data sets. This is intended to give you a critical insight into their operation, and an understanding of when and where such tools and techniques can best be applied.

You will also be given the chance, using the ‘R’ programming language, to implement several different kinds of data mining algorithms to gain a comprehensive understanding of their operation.

Curriculum insights

  • Extracting knowledge from data
  • Data pre-processing requirements
  • The data mining process
  • Tools and techniques of data mining
  • Data mining algorithms
  • Matching concepts to organisational requirements

Data Visualisation and Warehousing (8 weeks)

Objective
To introduce students to the concepts and challenges of creating data warehouses, and how data visualisation tools can be used to ‘tell a story’.

Description
By taking this module, you will gain practical experience of how to create data warehouses using data from multiple sources. It will also introduce you to best practices in data visualisation and data storytelling, using state-of-the-art data visualisation technology.

The module is intended to help you understand the approaches and benefits of data warehousing, and how to quickly gain and communicate insights into the data stored in data warehouses using data visualisation techniques.

Curriculum insights

  • Data warehousing concepts and technologies
  • Creating a data warehouse
  • The importance of data visualisation
  • Creating data visualisations
  • Telling a ‘data story’

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