Master of Machine Learning (MMLearn)
Master of Machine Learning (MMLearn)
Program Code
MML
Program Faculty
Faculty of Sciences, Engineering and Technology
Academic Year
2020
These Program Rules should be read in conjunction with the University's policies (https://www.adelaide.edu.au/policies).
Overview
The Master of Machine Learning will provide graduates with a foundation in Machine Learning and allow for the identification and application of emerging developments and considerations. Machine Learning is a specialisation within the disciplines of Computer Science and Artificial Intelligence. It is a rapidly evolving space with implications for the future of work and our daily lives.
The program is suitable for students with no prior experience in computer science as well as those with existing qualifications. In this program, students undertake a variety of core and elective courses, designed to provide knowledge of the techniques and theory of machine learning, and their basis in computer science and mathematics. A significant capstone project combines skills developed across the program. Students will elect to undertake either a technical or applied specialisation. Students will elect to undertake either a research project within their area of specialisation, or an industry-based project.
The Master of Machine Learning is an AQF Level 9 qualification with a standard full-time duration of 2 years.
Conditions
Condition of Enrolment
Interruption of program: Students must apply for permission from the Faculty before taking a Leave of Absence. Any extension of the leave without approval will result in the loss of place in the program but an application may be made to be re-admitted to the program subject to the admission procedures in place at the time.
Academic Program Rules for Master of Machine Learning
There shall be a Master of Machine Learning.
Qualification Requirements
To qualify for the degree of Master of Machine Learning, the student must complete satisfactorily a program of study consisting of the following courses with a combined total of not less than 48 units, comprising:
Core courses to the value of 27 units
Elective courses to the value of 9 units
A research project or industry based project to the value of 12 units
Unless exempted international students are required to take ELEC ENG 7057 Engineering Communication & Critical Thinking in lieu of an elective.
Core Courses
-
Master of Machine Learning
Core
All of the following courses must be completed:
Subject/Catalogue Course Title Unit Value COMP SCI 7210 Foundations of Computer Science - Python A 3 COMP SCI 7211 Foundations of Computer Science - Python B 3 COMP SCI 7212 Human and Ethical Factors in Computer Science 3 COMP SCI 7314 Introduction to Statistical Machine Learning 3 COMP SCI 7317 Using Machine Learning Tools PG 3 MATHS 7027 Mathematical Foundations of Data Science 3 PHIL 7005 Machine Learning and Artificial Intelligence 3 All of the following courses must be completed:
Technical Specialisation
Subject/Catalogue Course Title Unit Value COMP SCI 7059 Artificial Intelligence 3 COMP SCI 7318 Deep Learning Fundamentals 3 or
All of the following courses must be completed:
Applied Specialisation
Subject/Catalogue Course Title Unit Value COMP SCI 7416 Applied Machine Learning 3 POLIS 7024 Political Institutions and Policy-Making 3 Project
Research Pathway
Subject/Catalogue Course Title Unit Value COMP SCI 7205A Master of Machine Learning Research Project Part A 0 COMP SCI 7205B Master of Machine Learning Research Project Part B 12 or
Industry Pathway
Subject/Catalogue Course Title Unit Value COMP SCI 7206A Master of Machine Learning Industry Project Part A 0 COMP SCI 7206B Master of Machine Learning Industry Project Part B 12 Elective
Courses to the value of up to 9 units may be taken from the following:
Subject/Catalogue Course Title Unit Value COMP SCI 7007 Specialised Programming 3 COMP SCI 7039 Computer Networks & Applications 3 COMP SCI 7064 Operating Systems 3 COMP SCI 7076 Distributed Systems 3 COMP SCI 7088 Systems Programming 3 COMP SCI 7305 Parallel and Distributed Computing 3 COMP SCI 7306 Mining Big Data 3 COMP SCI 7307 Secure Programming 3 COMP SCI 7308 Cybersecurity Fundamentals 3 COMP SCI 7315 Computer Vision 3 COMP SCI 7407 Advanced Algorithms 3 COMP SCI 7417 Applied Natural Language Processing 3 COMP SCI 7418 Advanced Topics in Machine Learning 3 COMP SCI 7419 Deep Learning: Image Processing 3 MATHS 7103 Probability & Statistics 3