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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.
For further information see Computer Science and Software Engineering Head of Department
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; and; • the work of others – including generative AI – is cited correctly to acknowledge use of external materials.
To gain a passing grade in COSC480 students must: 1. achieve an average grade of at least 50% over all assessment items 2. achieve a passing grade in each of the two oral exams delivered* Upon satisfying the above criteria your grades will be determined by University-wide grade scale . However, if you do not satisfy both passing criteria you will be given either a D or E grade depending on marks.* If a student fails 2. above, they must pass a invigilated python proficiency exam.
This course is primarily delivered online, with only two assessments requiring in-person attendance. Students can attend a weekly:• lab session - Where you can ask programming questions. • tutorial session - Where you can seek support from the COSC480 tutor with your COSC480 projectYou can add these events to your personal timetable using My Timetable . You are also welcome to attend more than one of each event if you would like more assistance, so long as there is space available in the room.
Domestic fee $1,176.00
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 .