Bachelor of Computer Science

2016 Deakin University Handbook

Note: You are seeing the 2016 view of this course information. These details may no longer be current. [Go to the current version]
Year2016 course information
Award granted Bachelor of Computer Science
CampusOffered at Burwood (Melbourne)
Cloud CampusYes
Duration3 years full-time or part-time equivalent
CRICOS course code083695K Burwood (Melbourne)
Deakin course codeS306

Course sub-headings

Course overview

Deakin’s Bachelor of Computer Science will equip you with the knowledge and practical skills required to design and develop innovative software solutions to complex information and technology problems faced by communities, businesses and industries.

The course is ideally suited to those who are passionate about solving problems and creating solutions, curious about how something works, rather than simply what it does and interested in working at the leading edge of technology innovation and development.

This course provides a comprehensive and systematic study of computer systems and networks, data management and information processes, human computer interaction, programming and software development, computing theory, mathematical methods, and algorithm design and analysis.

Choose from major sequences in Data Science, Robotics and Cyber-Physical Computing, or Cognitive Computing to focus your expertise in areas such as machine learning, artificial intelligence, robotics, smart devices and autonomous systems.

As a student you’ll gain hands-on experience and a practical understanding of theory through learning activities in our modern computing laboratories, working with the latest hardware and software technologies alongside our internationally recognised academic staff. Our world-class research programs in computer science feed directly into our classrooms, meaning that you’ll be learning at the cutting edge of industry expectations and capabilities.

Deakin’s Bachelor of Computer Science has been accredited by the Australian Computer Society (ACS), ensuring a high quality of education and providing you with international recognition as an ICT industry professional.

Computer science graduates are in high demand in Australia and internationally and find employment in a variety of roles, such as data scientist, software developer, software engineer, systems or network administrator, database administrator or developer, solutions architect, systems analyst, or project manager. Computer scientists also work in specialist research and development roles, in both public and private organisations.

Units in the course may include assessment hurdle requirements.

Professional recognition

The Bachelor of Computer Science is provisionally accredited with the Australian Computer Society (ACS).

Career opportunities

You will be suited to find employment in organisations engaged in software development, Big Data analysis, cloud computing infrastructure. Initial graduates are typically employed as a software developer, software analyst and design, database and web developer, network and systems manager, and IT consultant.  As your experience develops, you will also be well prepared for progression into project management positions.


Equipment requirements

For information regarding hardware and software requirements, please refer to the School of Information Technology's website, www.deakin.edu.au/information-technology/students or telephone 03 9244 6699.

Course rules

To complete the Bachelor of Computer Science, students must attain 24 credit points. Most units (think of units as ‘subjects’) are equal to 1 credit point. So that means in order to gain 24 credit points, you’ll need to study 24 units (AKA ‘subjects’) over your entire degree. Most students choose to study 4 units per trimester, and usually undertake two trimesters each year.

The course comprises a total of 24 credit points, which must include the following:

  • 16 core IT units (which includes a compulsory internship unit)
  • 2 elective units
  • Completion of SIT010 Safety Induction Program (0 credit-point compulsory unit)
  • Completion of STP010 Introduction to Work Placements (0 credit-point compulsory unit)
  • At least one 6-credit point Computer Science major sequence from: Cloud Computing, Cognitive Science, Data Science or Robotics and Cyber-physical Computing.
  • level 1 - maximum of 10 credit points
  • levels 2 and 3 - minimum of 14 credit points over both levels
  • level 3 - minimum of 6 credit points of which at least 4 must be SIT Course Grouped units 

Major sequences

Refer to the details of each major sequence for availability.

Course structure

Core

Level 1 - Trimester 1

SIT010Unit description is currently unavailable (0 credit point unit)

SIT105Unit description is currently unavailable

SIT190Unit description is currently unavailable **

SIT111Unit description is currently unavailable

One SIT-coded unit (major)

Level 1 - Trimester 2

SIT102Unit description is currently unavailable

SIT103Unit description is currently unavailable

SIT192Unit description is currently unavailable

One SIT-coded unit (major)

 

Level 2 - Trimester 1

STP010Unit description is currently unavailable (0 credit point unit)

SIT222Unit description is currently unavailable

SIT223Unit description is currently unavailable

SIT232Unit description is currently unavailable

One SIT-coded unit (major)

Level 2 - Trimester 2

SIT202Unit description is currently unavailable

SIT221Unit description is currently unavailable

One elective

One SIT-coded unit (major)

 

Level 3 - Trimester1

SIT365Unit description is currently unavailable

SIT322Unit description is currently unavailable

SIT374Unit description is currently unavailable

One SIT-coded unit (major)

Level 3 - Trimester 2

SIT302Unit description is currently unavailable

SIT306Unit description is currently unavailable ^

One elective

One SIT-coded unit (major)

 

** Students who have completed Mathematical Methods 3 and 4 or equivalent may choose to replace SIT190 with an elective unit

^ Offered in Trimester 1, trimester 2 and trimester 3

Course structure

Electives

Select from a range of elective units offered across many courses. In some cases you may even be able to choose elective units from a completely different discipline area (subject to meeting unit requirements).

Details of major sequences

Cloud Computing

Campuses

Burwood (Melbourne), Waurn Ponds (Geelong)

Unit set code

MJ-S000063

Overview

Cloud Computing is a significant development in the IT industry that is having a major impact on how software solutions are developed, deployed, and delivered over the web. You will undertake a study of the concepts and technologies of cloud computing and acquire the necessary expertise to work effectively in this field, both by exploiting public cloud infrastructure options and through the construction of private cloud infrastructure.

The major sequence incorporates the Cisco Certified Networking Associate (CCNA) curriculum that trains you in the skills needed to construct and maintain network infrastructures to effectively support organisational needs.

Subject areas include: cloud computing and virtualisation, computer security, enterprise network construction and management, system security and research and development in IT.

Units

SIT113Unit description is currently unavailable

SIT182Unit description is currently unavailable

SIT272Unit description is currently unavailable

SIT277Unit description is currently unavailable

SIT340Unit description is currently unavailable

SIT382Unit description is currently unavailable

Details of major sequences

Robotics and Cyber-physical Computing

Campuses

Burwood (Melbourne), Cloud (online)

Unit set code

MJ-S000083

Overview

Robotics and cyber-physical systems have emerged as a major commercial technology sector, combining software and hardware to enable products from autonomous vehicles to fitness trackers and smart homes. Specialists in robotics and cyber-physical computing work alongside hardware engineers and generalist application developers, employing specific skills and knowledge to integrate and control diverse hardware devices; collect, communicate and analyse sensor data streams; and develop and employ novel algorithms that allow these systems to act in response to their environment. Common development practices in this field involve rapid prototyping and iterative refinement and demand new skill sets from computing professionals.

Units

SIT122Unit description is currently unavailable (offered Tri-1 from 2017)

SIT123Unit description is currently unavailable *

SIT210Unit description is currently unavailable ^

SIT213Unit description is currently unavailable ^

SIT310Unit description is currently unavailable #

SIT312Unit description is currently unavailable #

 * available from 2017

^ available from 2018

# available from 2019

Details of major sequences

Cognitive Science

Campuses

Burwood (Melbourne), Cloud (online)

Unit set code

MJ-S000073

Overview

Effective navigation through the current flood of large-volume, unstructured data requires a new era of computing known as cognitive systems. Cognitive systems learn and interact with people to extend what either humans or machines could do on their own. IBM Watson* is just one example of a cognitive system demonstrating the capacity to answer natural language questions, acquire information, process large amounts of disparate data and learn through repeat interaction.

New in 2016, this major sequence provides students with the fundamental knowledge and technical skills required to design and develop new cognitive computing applications fuelled by Watson’s intelligence (as well as other types of smart machines).

Subject areas include: psychology, understanding the mind, thinking systems and cognition science, human behaviour and computer interaction, and data visualisation and decision making.

Units

HPS111Unit description is currently unavailable

HPS121Unit description is currently unavailable

HPS203Unit description is currently unavailable

SIT205Unit description is currently unavailable *

SIT308Unit description is currently unavailable ^

SIT309Unit description is currently unavailable ^

*available from 2017

^available from 2018

Details of major sequences

Data Science

Campuses

Burwood (Melbourne), Cloud (online)

Unit set code

MJ-S000060

Overview

Data analytics is an integral part of decision making in all sectors of the society: business, finance, government, medicine, research and beyond. The Data Science major sequence provides you with the skills and knowledge that are essential for data analytics professionals. You will learn the theory, methodologies, and techniques that allow you to interpret datasets and uncover hidden patterns in order to make predictions, draw conclusions, drive successful initiatives, and make better decisions. Particular focus will be paid to meaningful analyses in the face of huge amounts of data, where traditional approaches may be impractical.

Subject areas include a wide spectrum of analytics: data science concepts, statistics and data analysis, computational decision analysis, data mining and machine learning, and advanced data science.

Units

SIT191Unit description is currently unavailable

SIT112Unit description is currently unavailable

SIT208Unit description is currently unavailable

SIT292Unit description is currently unavailable

SIT399Unit description is currently unavailable

SIT307Unit description is currently unavailable ^

^ available from 2017