Assessment Marks

It is the responsibility of students to view their marks for each within session assessment on iLearn within 20 working days of posting. If there are any discrepancies, students must contact the unit convenor immediately. Failure to do so will mean that queries received after the release of final results regarding assessment marks (not including the final exam mark) will not be addressed.

Special Consideration

Where a Special Consideration application is approved, the student may be offered an alternative assessment or may receive a mark based on the percentage mark achieved by the student in one or more other assessment tasks, at the Unit Convenor’s discretion.

Late Penalties

Tasks 10% or less – No extensions will be granted. Students who have not submitted the task prior to the deadline will be awarded a mark of 0 for the task, except for cases in which an application for special consideration is made and approved.

Tasks above 10% - No extensions will be granted. There will be a deduction of 10% of the total available marks made from the total awarded mark for each 24 hour period or part thereof that the submission is late (for example, 25 hours late in submission – 20% penalty). This penalty does not apply for cases in which an application for special consideration is made and approved. No submission will be accepted after solutions have been posted.

Classes 

• Number and length of classes: 3 hours face-to-face teaching per week, consisting of 1 x 2 hour lecture and 1 x 1 hour tutorial.
• The timetable for classes can be found on the University web site at: http://www.timetables.mq.edu.au/

Textbook

• ‘Advanced Analytics Methodologies: Driving Business Value with Analytics’, Michele Chambers, Thomas W Dinsmore, Pearson ISBN-13: 978-0133498608, ISBN-10: 0133498603

Technology Used and Required

Students will learn to use spreadsheet (MS-Excel), Tableau and Gephi. Students will choose to become intermediate-skilled at one of the existing Data Mining/ Analytics packages, such as SPSS Modeler, RapidMiner, Orange, Knime, R statistical package, and others. They will also be exposed to data editing software such as OpenRefine, EasyMorph and Tableau Data Editor.

Unit Web Page

The web page for this unit can be found at: iLearn http://ilearn.mq.edu.au

Teaching and Learning Strategy

This unit is lecture- and tutorial-based. Typically, the class-time structure will be like this:

• Lectures: We will establish links between theory and your personal knowledge from your previous units during class discussions, and then integrate these with applied exercises.
• Tutorials: students are required to work on some tasks using appropriate models and techniques. Student participation and meaningful contribution are essential to understand analytics concepts and techniques.

Lecture notes will be posted after each lecture on iLearn

Unit Schedule

Time spent on individual topics and exercises may change as we progress during the semester, so some topics may vary from this schedule.

Some minor changes to assessment criteria, and more details on assessment expectations.

This unit teaches Analytics that can be applied in a global context.

• This unit includes research by the unit lecturer and other Macquarie University researchers
• This unit uses research from external sources.
• This unit gives you opportunities to learn how to critique current research at the frontiers of your discipline as a prelude to later conducting your own research.