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An introduction for graduate students to imperative computer programming using Python. Topics include: expressions, assignment, selection and iteration, structured data (lists, dictionaries, tuples, arrays), functional decomposition, file processing, using library code, and an introduction to object-oriented programming. Students must develop a significant piece of program code in a project that demonstrates mastery of programming for practical applications, typically in data science.
This is an accelerated course aimed at graduate students without any prior programming background. It introduces the concepts of imperative programming, using Python, to develop programming skills aimed at data science-centred problems. Learners will develop their skills throughout the course through a project that involves data cleansing, data analysis and visualisation. Topics covered throughout the course to support the completion of this project include: • Expressions • Assignment • Selection and iteration • Structured data (lists, dictionaries, tuples, arrays) • Functional decomposition • Object-oriented programming • Data manipulation using Pandas • Visualisation with matplotlib
Fluently solve simple programming problems with a given programming language. Analyse programming code to predict program behaviour. Employ appropriate third-party programming libraries to deal with complex programming problems. Develop a program to cleanse data, including organising, identify trends and visualise data for ill-specified, complex data-science problems.
Subject to approval of the Head of Department.
Students must attend one activity from each section.
Walter Guttmann
There are several important documents available online about departmental regulations, policies and guidelines at the following site. We expect all students to be familiar with these. Notices about this class will be posted to the class forum in the Learn system.COSC students will also be made members of a class called “CSSE Notices”, where general notices will be posted that apply to all classes (such as information about building access or job opportunities).
All work completed as part of COSC480 must be substantially your own work. You must correctly cite the work of others – including generative AI – to acknowledge any use of external materials. You are not allowed to use any AI system for the test and the final exam.
If you achieve at least 50% in the test and at least 50% in the final exam your grade will be P (Pass). Otherwise your grade will be F (Fail).
This course is primarily delivered online. You must attend the test and the final exam on campus. You may also attend a weekly lab on campus to seek support from the tutor.
Domestic fee $1,247.00
International Postgraduate fees
* All fees are inclusive of NZ GST or any equivalent overseas tax, and do not include any programme level discount or additional course-related expenses.
For further information see Computer Science and Software Engineering .