Part A: Course Overview

Course Title: Mathematical Computing and Algorithms

Credit Points: 12.00

Terms

Course Code

Campus

Career

School

Learning Mode

Teaching Period(s)

MATH2109

City Campus

Undergraduate

145H Mathematical & Geospatial Sciences

Face-to-Face

 Sem 1 2006,
Sem 1 2007,
Sem 1 2008,
Sem 1 2009,
Sem 1 2010,
Sem 1 2011,
Sem 1 2012,
Sem 1 2013,
Sem 1 2014,
Sem 1 2015,
Sem 1 2016

MATH2109

City Campus

Undergraduate

171H School of Science

Face-to-Face

 Sem 1 2017,
Sem 1 2018,
Sem 1 2019,
Sem 1 2020,
Sem 1 2021,
Sem 1 2022

Course Coordinator: Assoc Professor Marc Demange & Professor Andrew Eberhard

Course Coordinator Phone: N/A

Course Coordinator Email: marc.demange@rmit.edu.au & andy.eberhard@rmit.edu.au


Pre-requisite Courses and Assumed Knowledge and Capabilities

None


Course Description

This course is designed to teach you how to conceive and implement a computer program using a mathematical programming language (package) like MATLAB. This is used in particular to construct computer models of mathematical and physical problems. MATLAB, Maple and Mathematica are three of the standard computing packages used by mathematicians. The knowledge and skills developed in this course are usually assumed by an employer. These are often used in conjunction with spreadsheets like Excel to enable the input of data. The skills you gain in this course will also be used in many of the other mathematics and statistics courses in your program. Skills will be developed through individual modelling exercises in the lab following on from appropriate lecture material. 


Objectives/Learning Outcomes/Capability Development

This course contributes to the following Program Learning Outcomes for BP083 Bachelor of Science (Applied Mathematics and Statistics): 

Knowledge and technical competence

  • the ability to use the appropriate and relevant, fundamental and applied mathematical and statistical knowledge, methodologies and modern computational tools.

Problem-solving

  • the ability to bring together and flexibly apply knowledge to characterise, analyse and solve a wide range of problems
  • an understanding of the balance between the complexity / accuracy of the mathematical / statistical models used and the timeliness of the delivery of the solution.


Upon successful completion of this course you should be able to:

  1. Write and debug small computer programs ;
  2. Model and / or solve a range of mathematical problems using either the in-built functions or by writing your own computer program;
  3. Interpret and report on the results obtained;
  4. Interface Matlab with Data Bases and the efficient handling of data from spreadsheets.  


Overview of Learning Activities

 

You will be actively engaged in a range of learning activities such as lectorials, tutorials, practicals, laboratories, seminars, project work, class discussion, individual and group activities. Delivery may be face to face, online or a mix of both. 

You are encouraged to be proactive and self-directed in your learning, asking questions of your lecturer and/or peers and seeking out information as required, especially from the numerous sources available through the RMIT library, and through links and material specific to this course that is available through myRMIT Studies Course


Overview of Learning Resources

 

RMIT will provide you with resources and tools for learning in this course through myRMIT Studies Course. 

There are services available to support your learning through the University Library. The Library provides guides on academic referencing and subject specialist help as well as a range of study support services. For further information, please visit the Library page on the RMIT University website and the myRMIT student portal.


Overview of Assessment

Assessment tasks

Assessment task 1: Practical formative hand in assessment 
Weighting 10%
This assessment task supports CLOs 1 & 2 

Assessment task 2: Practice based assessments:
Weighting 40%
This assessment task supports CLOs  1 & 2 

Assessment task 3: Authentic-practical evaluations of professional skills:
Weighting 50%
This assessment task supports CLO  1, 2, 3 & 4 

If you have a long-term medical condition and/or disability it may be possible to negotiate to vary aspects of the learning or assessment methods. You can contact the program coordinator or Equitable Learning Services if you would like to find out more.