Course Title: Electrical Engineering Analysis

Part A: Course Overview

Course Title: Electrical Engineering Analysis

Credit Points: 12.00


Course Code

Campus

Career

School

Learning Mode

Teaching Period(s)

EEET2248

City Campus

Undergraduate

125H Electrical & Computer Engineering

Face-to-Face

Sem 2 2006,
Sem 2 2007,
Sem 2 2008,
Sem 2 2009,
Sem 2 2010,
Sem 2 2011,
Sem 2 2012,
Sem 2 2013,
Sem 2 2014,
Sem 2 2015,
Sem 2 2016

EEET2248

City Campus

Undergraduate

172H School of Engineering

Face-to-Face

Sem 1 2017

Course Coordinator: Dr Katrina Neville

Course Coordinator Phone: +61 3 9925 2530

Course Coordinator Email: katrina.neville@rmit.edu.au

Course Coordinator Location: 10.07.08

Course Coordinator Availability: Email for appointment


Pre-requisite Courses and Assumed Knowledge and Capabilities

Pre-requisites:

None

Assumed Knowledge and Capabilities:

  • The ability to solve basic algebraic equations and sets of linear equations.
  • The ability to apply basic calculus to simple functions.

 


Course Description

The main aims of this course is to introduce you to the fundamental mathematical techniques commonly used in the Electrical and Computer Engineering field and to equip you with the ability to apply a problem solving methodology to common engineering problems.

During this course you will be presented with various types of engineering problems which you will then work through from problem identification, algorithm design through to software implementation to ultimately a solution.

As part of this course you will also be introduced to the syntax and development environment of the engineering scripting language MATLAB, which will be used as the problem solving tool in this course.

This course will lay the foundations for all future courses requiring computer programming and problem solving skills which are ubiquitous in all fields of engineering.


Objectives/Learning Outcomes/Capability Development

This course contributes to the following Program Learning Outcomes:

1.1 Comprehensive, theory based understanding of the underpinning natural and physical sciences and the engineering fundamentals applicable to the engineering discipline.

1.2 Conceptual understanding of the, mathematics, numerical analysis, statistics, and computer and information sciences which underpin the engineering discipline.

1.3 In-depth understanding of specialist bodies of knowledge within the engineering discipline.

2.1 Application of established engineering methods to complex engineering problem solving.

2.2 Fluent application of engineering techniques, tools and resources.

2.3 Application of systematic engineering synthesis and design processes.

3.2 Effective oral and written communication in professional and lay domains.


On completion of this course you should be able to:


1. Apply a consistent methodology for solving a variety of electrical engineering problems.
2. Develop simple mathematical algorithms and the logic flow necessary to design software solutions to engineering problems.
3. Efficiently use MATLAB as a powerful software analysis tool to solve engineering problems.


Overview of Learning Activities

Your learning occurs through the following experiences and evaluation processes:

Theoretical concepts and the required numerical methods necessary for the course will be introduced in lectures.

Lectorials will allow you to work individually and in groups in a problem-based learning environment where you will develop your skills in problem solving and implementing software solutions in MATLAB.

Weekly tutorials will allow you to work through problems relating to the concepts introduced in the lectures, and

Laboratories will allow you to put your skills into practice.


Overview of Learning Resources

RMIT will provide you with resources and tools for learning in this course through our online systems.

Lists of relevant reference texts, resources in the library and freely accessible Internet sites will be provided.

Access to the MATLAB software package will be provided through RMIT computer labs, myDesktop and the MathWorks Total Academic Headcount student license.


Overview of Assessment

☒This course has no hurdle requirements.

The assessment for this course will be based on the following components:

  • Tutorial tests
  • Lectorial projects
  • Laboratory reports

This course does not have a final examination.

 

Assessment tasks

 

Assessment Task 1: Tutorial Tests

Weighting 20% 

This assessment supports CLOs 1, 2 & 3

Assessment Task 2: Laboratory reports

Weighting 30%

This assessment task supports CLOs 1, 2 & 3

Assessment Task 3: Individual Lectorial Project

Weighting 25%

This assessment task supports CLOs 3

Assessment Task 4: Group Lectorial Projects

Weighting 25%

This assessment task supports CLOs 1, 2 & 3