Part A: Course Overview

Course Title: Advanced Linear Algebra with Vector Calculus

Credit Points: 12.00

Terms

Course Code

Campus

Career

School

Learning Mode

Teaching Period(s)

MATH2311

City Campus

Undergraduate

145H Mathematical & Geospatial Sciences

Face-to-Face

 Sem 2 2016

MATH2311

City Campus

Undergraduate

171H School of Science

Face-to-Face

 Sem 2 2017,
Sem 2 2018,
Sem 2 2019,
Sem 2 2020,
Sem 2 2021,
Sem 2 2022,
Sem 1 2024,
Sem 1 2025

Course Coordinator: Dr Graham Clarke

Course Coordinator Phone: +61 3 9925 3225

Course Coordinator Email: graham.clarke@rmit.edu.au

Course Coordinator Location: 15.3.14


Pre-requisite Courses and Assumed Knowledge and Capabilities

Recommended Prior Study 

You should have satisfactorily completed or received credit for the following course/s before you commence this course: 

AND 

OR

 

If you have completed prior studies at RMIT or another institution that developed the skills and knowledge covered in the above course/s you may be eligible to apply for credit transfer. 

Alternatively, if you have prior relevant work experience that developed the skills and knowledge covered in the above course/s you may be eligible for recognition of prior learning. 

Please follow the link for further information on how to apply for credit for prior study or experience. 

Assumed Knowledge

Students are assumed to have knowledge of fundamental Calculus (derivatives, integrals, and their applications) and Linear Algebra (vector and matrix properties and operations) when participating in this course.


Course Description

Advanced Linear Algebra with Vector Calculus introduces and studies operations and methods that are the fundamental tools of mathematicians and applied scientists. The course introduces Linear Algebra (vector spaces and subspaces, linear independence, basis, kernel, dimension; inner products, linear transformations, eigenvalues, eigenvectors and diagonalisation) and Calculus of Vector Functions (scalar and vector fields, surfaces and space curves, gradient, divergence and curl, multiple integrals, line integrals and surface integrals; integral Theorems - Green’s, Gauss’ divergence and Stokes’ theorem). The foundation is laid for more specialist mathematical modelling and multivariate statistics subjects undertaken in subsequent years in your program of study. 


Objectives/Learning Outcomes/Capability Development

This course contributes to the program learning outcomes for the following program(s):   

BH101AMS - Bachelor of Science (Dean's Scholar, Applied Mathematics and Statistics) (Honours) 
BP083P20 - Bachelor of Science (Applied Mathematics and Statistics)  

PLO 2 Knowledge and Technical Competence 
PLO 3 Problem Solving 
PLO 4 Teamwork and Project Management 
PLO 5 Communication 
PLO 6 Information Literacy 

BP083P10 - Bachelor of Science (Mathematics) 

PLO 2 Knowledge and Technical Competence 
PLO 3 Problem Solving 
PLO 4 Teamwork and Project Management 
PLO 5 Communication 
PLO 6 Information Literacy 
PLO 7 Ethics 

BP083P23 - Bachelor of Applied Mathematics and Statistics (Mathematics Major)  

PLO 1 Apply a broad and coherent knowledge of mathematical and statistical theories, principles, concepts and practices with multi-disciplinary collaboration.  
PLO 2 Analyse and critically examine the validity of mathematical and statistical arguments and evidence using methods, technical skills, tools and computational technologies.  
PLO 3 Formulate and model real world problems using principles of mathematical and statistical inquiry to inform evidence-based decision making. 

BH119 - Bachelor of Analytics (Honours)  

PLO2 Knowledge and Technical Competence 
PLO3 Problem Solving 

BP350 - Bachelor of Science  (Mathematics Major)  

PLO 1 Apply a broad and coherent knowledge of scientific theories, principles, concepts and practice in one or more scientific disciplines.  
PLO 2 Analyse and critically examine scientific evidence using methods, technical skills, tools and emerging technologies in a range of scientific activities. 
PLO 3 Analyse and apply principles of scientific inquiry and critical evaluation to address real-world scientific challenges and inform evidence based decision making. 

For more information on the program learning outcomes for your program, please see the program guide.   


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

  1. Identify the properties of scalar and vector fields, demonstrate your ability to perform operations on them, and articulate the significance of these ideas clearly.
  2. Apply basic methods of linear algebra to real vector spaces, and collaborate effectively to explain the importance of these concepts.
  3. Solve complex problems by generalising ideas from real vector spaces to a wider range of linear spaces.
  4. Use analytical reasoning to extend and assess concepts from single-variable integration to multiple integrals, showcasing critical thinking by evaluating their applications.  


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: In-class tests  
Weighting 50%  
This assessment task supports CLOs 1 & 2 

Assessment Task 2: Homework assignments  
Weighting 30%  
This assessment task supports CLOs 3 & 4 

Assessment Task 3: Final summative assessment 
Weighting 20%  
This assessment task supports CLOs 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.