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fit1008-introduction-to-computer-science

This unit introduces students to core problem-solving, analytical skills, and methodologies useful for developing flexible, robust, and maintainable software. Topics include data types; data structures; algorithms; algorithmic complexity; recursion; and translation to assembly language.

fit1043-introduction-to-data-science

This unit looks at processes and case studies to understand the many facets of working with data, and the significant effort in Data Science over and above the core task of Data Analysis. Data and its handling is also introduced: characteristic kinds of data and its collection, data storage, data preparation, data cleaning and stream processing.

fit2004-algorithms-and-data-structures

This unit covers problem specification, algorithmic design, analysis and implementation. Detailed topics include analysis of best, average and worst-case time and space complexity; recursion; advanced data structures such as heaps and B-trees; hashing; sorting algorithms; searching algorithms; graph algorithms; numerical computing

fit2014-theory-of-computation

This unit introduces formal languages, models of computation, and computational complexity. Topics include finite state automata, regular expressions, grammars, pushdown automata, computable functions, Turing machines, polynomial-time reductions, complexity classes P and NP, and NP-completeness.

fit2081-mobile-application-development

This unit introduces an industrial strength programming language (with supporting software technologies and standards) and object-oriented application development in the context of mobile application development for smartphones and tablets.

fit2086-modelling-for-data-analysis

This unit explores the statistical modelling foundations that underlie the analytic aspects of Data Science.

fit2102-programming-paradigms

The unit covers paradigms such as functional and declarative programming styles, comparing and contrasting them to programming styles that students are already familiar with, including object-oriented, imperative and procedural programming paradigms.

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