Overview

The course is an advanced version of the Bachelor of Computer Science, designed for high-achieving students who wish to study computing in depth with a strong research component through the four years of study. Computer science is the theory and practice of applying computers and software to problem solving. Its … For more content click the Read More button below.

Mode and location

On campus

Learning outcomes

These course outcomes are aligned with the Australian Qualifications Framework and Monash Graduate Attributes.

Upon successful completion of this course it is expected that you will be able to:

1.

demonstrate an advanced knowledge of the role of computer science and computational methods, and recognise the importance of theoretical underpinning for practical work

2.

demonstrate understanding of ethical issues in professional and research practice and its historical, contemporary and likely future scientific, industrial and social context

3.

critically analyse problems, design algorithms to solve them, program efficient software solutions and demonstrate the ability to transform and apply computational solutions to new context

4.

apply problem-solving strategies to develop efficient solutions in your area of specialisation; in particular in:

  • advanced computer science you will be able to design, implement and critically evaluate substantial pieces of software using a range of programming paradigms, advanced data structures and algorithms
  • data science you will be able to design, implement and critically evaluate methods for capturing, managing and analysing data
5.

communicate and coordinate proficiently by: listening, speaking, reading and writing English and utilising diagrams, graphics and interactive visualisations in a professional and research context; working as an effective member or leader of teams; and using basic tools and practices of formal project management

6.

plan and execute projects with some independence and take responsibility for your own learning and practice; manage your own time and processes effectively by prioritising competing demands to achieve personal and team goals, with regular review of personal performance as a primary means of managing continuing professional development; behave in an ethical and professional manner, and be able to adapt readily to changing technologies

7.

critically evaluate IT research; be able to apply appropriate research methodologies to conduct significant independent research.

 

Professional recognition

This course is accredited by the Australian Computer Society as meeting the standard of knowledge for professional level membership.

Structure

The course develops through the themes of computer science foundation study, specialist discipline knowledge, research skills, and professional skills, which come together in applied practice.

Part A. Foundational computer science study

This study will develop your understanding of the role and theoretical basis of computer science and computational methods.

Part B. Professional skills

This study develops professional skills by providing an understanding and appreciation of the ethical and professional guidelines applicable to computer science practice and research; developing the ability to work as an effective team member and to communicate proficiently and appropriately in professional and research contexts.

Part C. Specialist discipline knowledge

This study will develop deep knowledge and advanced skills in advanced computer science or data science.

Part D. Research skills

This study develops the ability to critically evaluate IT research and to apply appropriate methodologies to conduct independent research in computer science or data science. It develops strong problem-solving skills and the ability to apply analytical thinking.

Part E. Applied practice

The above knowledge and skills are integrated and consolidated in applied practice as demonstrated in a computer science or data science project, and in some cases in an industry-based learning placement.

Part F. Free elective study

These elective units will enable you to broaden and deepen your knowledge of computer science or data science, or to select units from across the University in which you are eligible to enrol.

Course progression map

The course progression map provides guidance on unit enrolment for each semester of study.

Requirements
192 credit points

Course rules
Part B. Professional skills study12 credit points
Part C. Specialist discipline knowledge48 credit points
Part E. Applied practice12 credit points
Part F. Free elective study48 credit points

Additional information

Minimum pass grades

Course director(s)

Dr Julian Garcia Gallego