Part A: Course Overview

Course Title: Mathematics 2

Credit Points: 12.00

Important Information:

Please note that this course may have compulsory in-person attendance requirements for some teaching activities.


Terms

Course Code

Campus

Career

School

Learning Mode

Teaching Period(s)

MATH2168

City Campus

Undergraduate

155T Vocational Health and Sciences

Face-to-Face

 Sem 1 2008,
Sem 2 2008,
Sem 1 2009,
Sem 2 2009,
Sem 1 2010,
Sem 2 2010,
Sem 1 2011,
Sem 2 2011,
Sem 1 2012,
Sem 2 2012,
Sem 1 2013,
Sem 2 2013,
Sem 1 2014,
Sem 2 2014,
Sem 1 2015,
Sem 2 2015,
Sem 1 2016,
Sem 2 2016

MATH2168

City Campus

Undergraduate

174T School of VE Engineering, Health & Science

Face-to-Face

 Sem 1 2017,
Sem 2 2017,
Sem 1 2018,
Sem 2 2018,
Sem 1 2019,
Sem 2 2019,
Sem 1 2020,
Sem 2 2020,
Sem 1 2021,
Sem 2 2021

MATH2168

City Campus

Undergraduate

520T Future Technologies

Face-to-Face

 Sem 1 2022,
Sem 2 2022,
Sem 2 2023,
Sem 1 2024,
Sem 2 2024,
Sem 1 2025

MATH2240

RMIT University Vietnam

Undergraduate

155T Vocational Health and Sciences

Face-to-Face

 Viet1 2015,
Viet3 2015,
Viet1 2016

MATH2240

RMIT University Vietnam

Undergraduate

174T School of VE Engineering, Health & Science

Face-to-Face

 Viet1 2018,
Viet3 2018,
Viet3 2019

Course Coordinator: Dr Bishwajit Chowdhury

Course Coordinator Phone: +61 3 9925 8054

Course Coordinator Email: bishwajit.chowdhury@rmit.edu.au

Course Coordinator Location: 57.05.17


Pre-requisite Courses and Assumed Knowledge and Capabilities

NA


Course Description

This course develops the mathematical concepts introduced in MATH2167 and introduces topics such as: Matrix theory and linear algebra, Statistics and Probability, Analytic and Numerical methods of solving differential equations, Power series and MATLAB preparing students for application of these concepts to Engineering studies.


Objectives/Learning Outcomes/Capability Development

This course contributes to the following program learning outcomes:

1.1 Descriptive, formula-based understanding of the underpinning natural and physical sciences and the engineering fundamentals applicable to the practice area.

1.2 Procedural-level understanding of the mathematics, numerical analysis, statistics, and computer and information sciences which underpin the practice area.

1.4 Discernment of engineering developments within the practice area.

2.1 Application of established technical and practical methods to the solution of well- defined engineering problems.

2.2 Application of technical and practical techniques, tools and resources to well defined engineering problems.

 


On completion of this course you should be able to:

  1. Apply concepts and principles of matrix algebra to solve linear system of equations and determine eigenvalues and eigenvectors.
  2. Use statistics and probability to perform effective and accurate data analysis, interpretation, prediction and hypothesis testing.
  3. Use analytic and numerical methods to solve first and second order differential equations and apply this knowledge to engineering situations.
  4. Generate, recognise the basic properties and manipulate power series.
  5. Utilize MATLAB routines to support learning in the above topics in the context of engineering.


Overview of Learning Activities

The learning activities for this course include:

Attending

  • Lectures and tutorials
  • Computer Labs

Completing

  • Tutorial Exercises
  • MATLAB Exercises
  • Required Assessment tasks

Self-study: Private study entailing working through the course as presented in classes and supporting learning materials, and gaining practice and confidence in solving conceptual and numerical problems.

Key concepts and their application will be explained and illustrated (with examples) in lectures and other supporting learning resources.

Supervised problem-based practice classes and class tests/quizzes will build your capacity to solve problems and to think critically and analytically, and give you feedback on your understanding and academic progress.


Overview of Learning Resources

Learning resources will consist of recommended references and class notes which may be accessed through "myRMIT".

The references include books, journals, reports, notes and web-based resources.


Overview of Assessment

☒ This course has no hurdle requirements.

☐ All hurdle requirements for this course are indicated clearly in the assessment regime that follows, against the relevant assessment task(s) and all have been approved by the College Deputy Pro Vice-Chancellor (Learning & Teaching).

Assessment 1

MATLAB Tests 

Weighting towards final grade: 30%
Assessment 1 assesses the following course learning outcomes: 

PLO 1.1, 1.2, 1.4, 2.1, 2.2  CLO 1, 2, 3, 5  

Assessment 2

Mid-semester Test 
Weighting towards final grade: 30%
Assessment 2 assesses the following course learning outcomes: 
PLO 1.1, 1.2, 1.4, 2.1, 2.2  CLO 1, 2 

Assessment 3

Final Assessment 

Weighting towards final grade: 40%
Assessment 3 assesses the following course learning outcomes; 

PLO 1.1, 1.2, 1.4, 2.1, 2.2  CLO 1, 2, 3, 4