C6007 Master of Artificial Intelligence

The course comprises 96 points structured into three parts: Part A. Foundations for advanced artificial intelligence studies, Part B. Core master's study, and Part C. Advanced practice. All students complete Part A, Part B and Part C. Depending upon prior qualifications, you may receive credit for Part A.

Part A. Foundations for advance artificial intelligence studies

These studies will provide an orientation to the field of artificial intelligence at graduate level. They are intended for students whose previous qualification is not in a cognate field.

Part B. Core master's studies

These studies will provide an orientation and draw on best practices within the broad field of artificial intelligence practice and research. You will gain a critical understanding of theoretical and practical issues related to artificial intelligence. Your studies will focus on fundamentals, core knowledge as well as application in artificial intelligence. 

Part C. Advanced practice

The focus of these studies is professional or scholarly work that can contribute to the portfolio of professional development in AI. You will have two options: 

• A program of coursework involving advanced study and an industry experience studio project.
• A research pathway including a thesis. If you wish to use this master’s course as a pathway to a higher degree by research you should take this option.

Master's entry points

Depending on prior qualifications you may receive entry level credit (a form of block credit) which determines your point of entry to the course:

• If you are admitted at entry level 1 you complete 96 credit points, comprising Part A, Part B and Part C. 
• If you are admitted at entry level 2 you complete 72 credit points, comprising Part B and Part C.

Course progression map

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

The course comprises 96 points structured into three parts: Part A. Foundations for advanced artificial intelligence studies (24 points), Part B. Core master's study (48 points), and Part C. Advanced practice (24 points).

Units are 6 points unless otherwise stated.

Part A. Foundations for advanced artificial intelligence studies (24 points)

You must complete four units (24 points):

• FIT9131 Programming foundations in Java
• FIT9136 Algorithms and programming foundations in Python
• FIT9137 Introduction to computer architecture and networks
• MAT9004 Mathematical foundations for data science and AI

Part B. Core master's studies (48 points)

You must complete:

a. three units (18 points):

• FIT5197 Statistical data modelling
• FIT5047 Fundamentals of artificial intelligence
• FIT5125 IT research methods

 b. five units (30 points) selected from:

• FIT5201 Machine learning
• FIT5215 Deep learning
• FIT5216 Modelling discrete optimisation problems
• FIT5217 Natural language processing
• FIT5218 Human-centric AI 
• FIT5219 Advanced learning and cognitive systems
• FIT5220 Solving discrete optimisation problems
• FIT5221 Intelligent image and video analysis
• FIT5222 Planning and automated reasoning
• FIT5226 Multi agent systems and collective behaviour

Part C.  Advanced practice (24 points)

 You must complete either a. or b. below:

a. Industry experience (24 points)

• FIT5120 Industry experience studio project (12 pts)
• FIT5122 Professional practice
• One elective unit (6 points) selected from any [[http://www.monash.edu.au/pubs/handbooks/units/index-bycode-f.html][FIT-coded]] level 5 units, if you have the required prerequisites and there are no restrictions on enrolments.

 b. Minor thesis research* (24 points)

• FIT5126 Masters thesis part 1
• FIT5127 Masters thesis part 2
• FIT5128 Masters thesis final
• One elective unit (6 points) selected from any [[http://www.monash.edu.au/pubs/handbooks/units/index-bycode-f.html][FIT-coded]] level 5 units, if you have the required prerequisites and there are no restrictions on enrolments.

Enrolment in the research units is dependent on available supervisors and projects. Eligible students will be ranked based on their entire academic record and assessed for suitability to undertake the research component of this program.

Note*: To be eligible for the research option, you must have successfully completed 24 points of level 5 FIT-coded units and have achieved an overall average of at least 75% across all completed FIT-coded level 5 units, and have achieved at least a distinction in FIT5125 IT research methods.