Unprecedented volumes of data are being created on an almost daily basis and the amount of data we generate is expected to double every two years. This ‘Big Data’ has the power to change the way we work, live, and think. This subject is designed to provide students with the knowledge and skills to analyse Big Data in a variety of business contexts. Specifically, mathematical and practical applications of Artificial Neural Networks, Support Vector Machines, Natural Language Processing and Ensemble Decision Tree techniques are explored. Valuable skills in the use of these techniques is reinforced with practical applications in R.
|Faculty||Bond Business School|
|Study abroad||Available to Study Abroad students|
1. Recognise and communicate the inputs, outputs, relationships, boundaries, and data transformations of digital systems.
2. Design, train and use neural networks, SVN and ensemble tree models for business data systems.
3. Apply statistical techniques and mathematical reasoning to formulate machine learning tools for data analysis.
4. Apply the language, thinking and tools of data retrieval and manipulation to real-world problems.
5. Apply the communication framework for translating data analysis into decision making outcomes.
6. Articulate ideas, decisions, recommendations and other information in a clear, concise writing style tailored to a given audience.
Students must have successfully completed INFT12-216 Data Science or equivalent prior to undertaking INFT12-223