Course Title: Mathematics for Advanced Computing

Part A: Course Overview

Course Title: Mathematics for Advanced Computing

Credit Points: 12.00


Terms

Course Code

Campus

Career

School

Learning Mode

Teaching Period(s)

MATH2039

City Campus

Postgraduate

145H Mathematical & Geospatial Sciences

Face-to-Face

Sem 1 2006

MATH2040

Bundoora Campus

Undergraduate

145H Mathematical & Geospatial Sciences

Face-to-Face

Sem 1 2006

MATH2041

City Campus

Undergraduate

145H Mathematical & Geospatial Sciences

Face-to-Face

Sem 1 2006,
Sem 2 2007,
Sem 2 2008,
Sem 2 2009,
Sem 2 2010,
Sem 2 2011,
Sem 2 2012,
Sem 2 2014,
Sem 2 2015,
Sem 2 2016

MATH2041

City Campus

Undergraduate

171H School of Science

Face-to-Face

Sem 2 2017

MATH2110

Taylors College KL

Undergraduate

145H Mathematical & Geospatial Sciences

Face-to-Face

Offsh 3 10,
Offsh 1 11

Course Coordinator: Dr Claude Zorzan

Course Coordinator Phone: +61 3 9925 3270

Course Coordinator Email: claude.zorzan@rmit.edu.au

Course Coordinator Location: 8.9.76

Course Coordinator Availability: by appointment


Pre-requisite Courses and Assumed Knowledge and Capabilities

 

To successfully complete this course, you are expected to have capabilities consistent with the completion of VCE Mathematical Methods at Year 12 level. That is, you are expected to be able to correctly perform basic algebraic and arithmetic operations; solve quadratic and other algebraic equations; solve simultaneous linear equations; recognise and apply the concepts of function and inverse of a function; recognise the properties of common elementary functions (e.g. polynomials and trigonometric functions); sketch the common elementary functions; solve mathematical problems involving functions; find the derivative of elementary functions from first principles and combinations of elementary functions using the product, quotient and chain rules; find the anti-derivative (integral) of elementary functions; use integral calculus to determine the area under a curve.


Course Description

This course aims to provide a broad introduction to the fundamental mathematical procedures (differentiation and integration) and mathematical objects (vectors, differential equations, matrices) of continuous (i.e. non-discrete) mathematics needed by computer scientists. The course builds on the foundations laid in secondary school mathematics and supports later courses in the computer science program, particularly those involved with algorithmic complexity, machine learning and evolutionary computing, computer graphics, scientific computing, physical modelling and visualisation. Topic areas include differentiation with applications, functions and their derivatives, integration and its applications, methods of integration, vectors, matrices, vector valued functions, differential equations.


Objectives/Learning Outcomes/Capability Development

 

This course contributes to Program Learning Outcomes in various applied science programs. In particular it promotes knowledge, skills and their application in the following domains:

  • theoretical knowledge: you will develop your knowledge of differential and integral calculus, elementary functions, vectors, matrices and differential equations.
  • technical ability: with its emphasis on problem solving, this course will prepare you to be able to analyse the physical world in a systematic manner.
  • critical analysis and problem solving: you will be afforded opportunities to mathematically formulate and solve problems creatively, especially those in which a description of the problem is given in words only.
  • communication: your capabilities will be improved through regular feedback on your written work.


On successful completion of this course, you will be able to:

  1. Apply core mathematical skills such as arithmetic, algebraic manipulation, elementary geometry and trigonometry to a range of problems;
  2. Formulate and solve problems involving change and approximation by applying the techniques of integral and differential calculus and formulate and solve first-order differential equations;
  3. Recognise properties of the common mathematical functions (polynomials, exponentials, logarithms) and their combinations commonly found in computer science (e.g. in algorithmic complexity theory, information theory);
  4. Utilise techniques of vector and matrix analysis to problems involving three-dimensional geometry, motion and transformations in three-dimensional space, such as would be used by a subsequent course in computer graphics;


Overview of Learning Activities

Key concepts and their application will be explained and illustrated (with many examples) in lectures and in online notes. Supervised problem-based practice classes will build your capacity to solve problems, encourage you to think critically and analytically and provide feedback on your academic progress. Online tests and quizzes, where available, will consolidate your basic skills, e.g. in algebra and trigonometry and your basic knowledge of the topics presented in class. Homework problems set from the textbook and self-help tutorial questions will provide a focus for your private study.


Overview of Learning Resources

 

This course will be supported online through myRMIT and will give you access to  important announcements, staff contact details, the teaching schedule, online notes, tests and quizzes, self-help exercises and past exam papers.

WebLearn tests and quizzes

You are advised to login to myRMIT and read your student e-mail account daily for important announcements. You should also visit Blackboard at least once a day to view important announcements regarding the course and key documentation.

A library subject guide is available at: http://rmit.libguides.com/mathstats


Overview of Assessment

 

Assessment Tasks

 

Early Assessment Task: In Class tests (Weeks 2,4,6,8,10,12)

Weighting 20%

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

Assessment Task 2:  Weblearn tests (Weeks 2,4,6,8,10,12)

Weighting 20%

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

 

Assessment Task 3: Mid-semester Exam (Week 5)

Weighting 10%

This assessment task supports CLO 1 & 4

Assessment 4: Final Exam

Weighting 50% 

This assessment supports CLOs 1, 2, 3 & 4