This module is not currently running in 2024 to 2025.
The amount of data generated worldwide is more than doubling every year. Traditional data analysis techniques are inadequate for dealing with the vast ocean of data. This module introduces modern techniques, platforms and tools for analysing large data sets efficiently, along with key applications, to equip students to join the new generation of data scientists sought after by industry and academia.
Total contact hours: 24
Private study hours: 126
Total study hours: 150
50% Examination, 50% Coursework
Reading list (Indicative list, current at time of publication. Reading lists will be published annually)
Steve Lohr, Data-ism: The Revolution Transforming Decision Making, Consumer Behavior, and Almost Everything Else, HarperCollins, 2015
Cathy O'Neil, Rachel Schutt, Doing Data Science: Straight Talk from the Frontline, O'Reilly, 2013
Viktor Mayer-Schonberger, Kenneth Niel Cukier, Big Data: A revolution that will transform how we live, work, and think, Houghton Mifflin Harcourt Publishing Company, 2013
James Gleick, The Information: A History, a Theory, a Flood, ISBN: 0375423729, Pantheon, 2011
Bart Baesens, Analytics in a Big Data World: The essential guide to data science and its applications, 2014
See the library reading list for this module (Canterbury)
8. The intended subject specific learning outcomes.
On successfully completing the module students will be able to:
8.1. Demonstrate a systematic knowledge of data science and related concepts;
8.2. Identify strategies for the design, implementation and evaluation of data science approaches to a given problem;
8.3. Understand the different frameworks for effective information management and evaluate critically how to apply a given data science framework for a specific purpose;
8.4. Understand the legal background, security and ethical issues involved in data science;
8.5. Create and interpret new knowledge in data science to present and deliver innovative solutions to a range of problems and to a variety of audiences.
9. The intended generic learning outcomes.
On successfully completing the module students will be able to:
9.1. Comprehend the trade-offs involved in design choices;
9.2. Understand theoretical concepts and apply them to the design, implementation, management and evaluation of computer-based systems;
9.3. Use general IT facilities effectively;
9.4. Apply a variety of organisational skills including the management of people, operations management, marketing and the development of organisational strategy;
9.5. Understand professional responsibility, economic, social, moral and ethical issues;
9.6. Communicate technical issues and solutions effectively to a range of audiences.
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