Course Title: Mathematical Computing and Algorithms

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

Course Coordinator: Assoc Professor Joseph Apaloo

Course Coordinator Phone: N/A

Course Coordinator Email: joseph.apaloo@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.


On 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

The course consists of lectorials and computer labs. Recorded l Lectures will be available. Key concepts and their application will be explained and illustrated (with many examples) in lectorials and in online notes and videos. .  In computer lab classes,  you will build capacity in writing simple programs to solve mathematical problems. This will teach you to think critically and analytically and will allow feedback on your understanding and academic progress. The only way to learn how to programme is to write programs, starting with very small programs and building up the complexity.   


Overview of Learning Resources

You have access to the computer laboratory, program documentation, external internet links and access to RMIT Library online and hardcopy resources.

Lab and assignment sheets will be provided as well as access to the same sheets in electronic form on Canvas.

Students may also find the following Library guide useful: http://rmit.libguides.com/mathstats


Overview of Assessment

Assessment tasks

 

Practical formative hand in assessment  

Weighting 10% 

This assessment task supports CLOs 1 & 2 

 

Practice based assessments:

Weighting 40% 

This assessment task supports CLOs  1 & 2 

  

Authentic-practical evaluations of professional skills:

Weighting 50 % 

This assessment task supports CLO  1, 2, 3 & 4