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Master Of Software Engineering (Artificial Intelligence, Advanced)

Billy Blue College of Design

Are you professional in A.I. looking to enhance your career aspects and deepen your learning? Our rigorous, 64-week Master of Software Engineering (Artificial Intelligence Advanced) is for experienced software engineers looking to significantly deepen their knowledge and pursue specialist careers in the field of AI.

The Master of Software Engineering (Artificial Intelligence, Advanced) addresses industry demand for highly technical software engineers, developers & researchers with skills that encompass machine learning, computer vision, natural language processing and speech recognition. It offers professionals the opportunity to upskill in order to improve career prospects, provides recent graduates with the chance to continue and specialise in artificial intelligence. The course is anchored by machine learning to the field of artificial intelligence in the wider software engineering body of knowledge.

CAREERS IN ARTIFICIAL INTELLIGENCE

  • Senior Software Engineer
  • Senior Systems Engineer
  • AI Researcher
  • Research & Development Engineer
  • Technical Director
  • Development Director
  • Systems Architect
  • Data Scientist

QUICK COURSE GUIDE

Qualification Title MASTER OF SOFTWARE ENGINEERING (ARTIFICIAL INTELLIGENCE, ADVANCED)    

Study Options – Domestic Australian students

Full-time Blended*

Part-time Blended*

Full-time Online

Part-time Online

*Blended (face to face on campus plus facilitated online)

Study Options - International students

Full-time Blended*

*Blended - face to face on campus plus facilitated online (no more than 30% online)

Start Dates

February, June, September

Course Length

Full-time: 2 years

Accelerated: 4 years

Part-time: 4 years maximum

Admission Criteria

The standard entry requirement is a completed qualification at AQF Level 7 (Bachelor degree) or above from an Australian University in a relevant field of study or an equivalent overseas higher education qualification or equivalent.

Students without an undergraduate degree, may be admitted on the basis of

  • At least 3 years professional experience in software development (documented e.g. CV), demonstrating a reasonable prospect of success; AND

  • A discipline specific portfolio; AND

  • A recommendation letter from 2 most recent employers (applicable to international students, and in addition to academic or special entry requirements noted above)

Entry Requirements for Overseas Students

Torrens offers a free, personalized admission process where each applicant is considered on an individual basis. Please contact your International Admissions Officer to have your previous studies assessed for equivalence.

Approved English tests include:

    IELTS level 6.5 required, with no element less than 6 (or equivalent TOEFL, CAE or PTE).

Payment Options - Domestic Australian students

Upfront payment

This means tuition fees will be invoiced each trimester and payment is required on or before the due date.

FEE-HELP

FEE-HELP is Australian Government’s loan scheme for higher education degree courses.

It can assist you in paying for all, or part of, your course fees. Repayments commence via the tax system once your income rises above a minimum threshold. Just like with any other debt, a FEE-HELP debt is a real debt that impacts your credit rating.

PAYMENT OPTIONS - INTERNATIONAL STUDENTS

Upfront payment

This means tuition fees will be invoiced each trimester and payment is required on or before the due date.

Course study requirements

Each subject involves 10 hours of study per week, comprising 3 hours of facilitated study and 7 hours self-directed study.

Assessment

Project/Application/Research Proposal, Process/Research Documentation, Application Outcome, Reflective Journal/ Blog, Report/Essay, Presentation/ Pitch, Examinations/Tests/ Quizzes, Research, Collaboration, Individual self-directed major project, Work integrated learning project work, Software development for social enterprise.

Location

Sydney Campus

Melbourne Campus

Provider

Torrens University Australia

Provider obligations

Torrens University Australia is registered as a self-accrediting Australian university by the Tertiary Education Quality and Standards Agency (TEQSA).

Accrediting body

Torrens University Australia Ltd

Course Fees

For details, please click here

CRICOS Course Code

099353A

Key Dates

2019 course dates for all Billy Blue classes held at our Sydney, Melbourne and Brisbane campuses.

Start Dates Census Dates Last Day Breaks
Mon 7 Jan 2019 18 Jan 27 Feb 18 Feb – 25 Feb
Mon 25 Feb 2019 15 Mar 19 May 20 May – 9 June
Mon 10 June 2019 28 June 01 Sep 2 Sep – 22 Sep
Mon 16 Sep 2019 4 Oct 8 Dec 9 Dec – 16 Feb 2020

Course Structure

The course structure comprises 11 core subjects and 2 elective subjects over Levels 400, 500, and 500, as follows:

Level 400 4 core subjects
Level 500 3 core subjects 1 elective subject
Level 600 4 core subjects 1 elective subject

Course rules

The Master of Software Engineering (Artificial Intelligence, Advanced) is two years in duration for a full-time student, or four years duration for a part-time student. Each year consists of three Study Periods, also known as Trimesters.

COURSE SUBJECTS - Master Of Software Engineering (Artificial Intelligence, Advanced)

In this subject students are introduced to the current Software Engineering standards and processes, with the aim of enabling them to analyse, design, and implement software projects that follow certain quality measures at every stage of the Software Development Life Cycle. The subject covers requirements engineering, modelling and design of software, software architecture, verification and validation of software systems, and other topics that are related to software engineering practices.

This subject helps students explore several non-technical aspects of software development, especially pertaining to human behavior and interactions so that students can appreciate the human aspects of technology. Broadly, the subject covers the theory of knowledge, human cognition, ethical and moral values, analysis of human history, critical analysis, creative aspects of the human mind and social interaction among human beings through a technological context. Students will use the specialised skills that they gain in other subjects to help formulate and suggest innovative solutions to problems that affect diverse societies

This subject deals with integrating the entire development lifecycle of IT systems in a secure environment through secure design methodologies, software development models, architecture design and industry Secure by Design standards like OWASP (Open Web Application Security Project). This subject also deals with how to build adequate security into systems to maintain integrity and safety of the functionality of IT systems while being exposed to cyber threats.

In this subject the students are introduced to the main project management principles and modern software project management practices. During the subject, the different methods for managing and optimising the software development process are discussed along with the different techniques for performing each phase of the software development life cycle.

The purpose of this subject is to provide a solid mathematical background that students will encounter in studies of Artificial Intelligence, specifically in sub-areas such as machine learning, natural language processing, speech recognition, and computer vision. This subject will cover topics including linear algebra (equations, functions and graphs), differentiation and optimisation, vectors and matrices, statistics and probabilities. Thorough understanding of these mathematical concepts is necessary for understanding the inner workings of the algorithms in Artificial Intelligence.

This subject introduces students to a framework for developing good scholarly inquiry skills and fundamental knowledge needed to make rational decisions about research strategies. Students will be presented with research strategies to critically investigate exemplar studies and examine the connection between a research question with appropriate research design and methodology. On completion of this subject, students should be able to develop researchable questions, and write research proposals and literature reviews. They will have a critical understanding of the strengths and limitations of the quantitative, qualitative and mixed method approaches to research. They will also learn about the ethical principles of research, challenges in getting approval and the approval processes.

This subject aims to give a broad introduction of intelligent systems, that is, how technologically advanced machines perceive and respond to the world around them. Discussion will focus on how Artificial Intelligence (AI) concepts and classifications are used to design intelligent systems. Overview of AI topics such as representation, reasoning, search methods, intelligent agents, learning, uncertainties and probabilities, perception and action, and communication are presented. It also includes discussions of AI classifications such as Machine Learning, Robotic, Natural Language Processing, Speech Recognition, Expert Systems, Computer Vision, and how they are used to make intelligent systems. This subject also enables students to understand the particular ethical issues that AI presents and how it can be used to benefit society.

This subject is designed to give a graduate-level student an in-depth understanding of the methodologies, technologies, mathematics and algorithms currently used in machine learning. Students will learn the theory behind a range of machine learning tools and practice applying the tools to different applications. It covers topics such as classification, linear models, learning theory, generative models, graphical models and learning paradigm. This subject covers theoretical concepts such as inductive bias, the PAC learning framework, Bayesian learning methods, margin-based learning, and Occam’s Razor. Students are given short programming assignments that include hands-on experiments using machine learning algorithms and methods

This subject introduces the basics of deep learning and how to build neural networks. Students are presented with different methods and applications to different AI sub-areas such as natural language processing, speech recognition, and computer vision. The subject begins with the introduction of simple neural networks such as multi-layer perceptron, and to more complicated concepts such as recurrent neural networks, convolutional networks, and long short-term networks.

This subject is designed to provide students an opportunity to pursue a significant project in a professional environment related to their specialisation. This enables students to develop skills that enhance their prospects of gaining meaningful employment and build their career for the future. Work integrated learning broadens the students’ learning environment while they are studying and allows them to see first-hand how their learnings in their degree translates in practice, as well as how ‘real world’ practice relates to what they are learning at University. Students enrolled in Masters (Advanced) have an opportunity to avail one of the three options below simultaneously for this subject and “Advanced Technology – Work Integrated Learning”.

There are three options available to students:

  • Option 1: Industry Placement Students are offered the opportunity to work within a technology company as an intern or volunteer at a technology non-profit organisation. It encourages students to build long-term relationships with the tech industry and provides an opportunity for them to work with and learn from people who may end up becoming colleagues, managers or mentors. It also provides a context in which to enhance their communication skills and work collaboratively in a professional arena. Students will undertake a series of industry-led tasks that are relevant to their field of study in order to understand the key concepts of working in and managing a professional technology team with emphasis placed on the operation of the environment.

  • Option 2: Industry Live Brief Industry live brief, also known as an industry project engages students in an activity where the parameters of success are set by the client. Academic staff and industry provide supervision for students, while industry provides, mentorship in addition. Numerous technology firms have ideas and opportunities they would like to explore and prototype; this is where students or student teams connect with industry to achieve scale with minimal risk. An understanding of research methodologies appropriate to professional practice and the documentation of personal creative investigation is explored. Students also further investigate and examine entrepreneurial and commercial opportunities through collaborative work practice. The subject fosters a cross specialisation perspective and draws on both specialised and common software engineering practices. Students are required to work both independently and as part of a collaborative team that includes industry representatives to conduct research, analyse and define project parameters and deliver innovative solutions that expand the notion of an industry live brief.

  • Options 3: Capstone Students execute, finalise and present their self-initiated project exhibiting a sophisticated understanding of software engineering, whilst addressing the university ethos. Central to the project will be evidence of critical analysis and reflexive and reflective practice, social engagement, in addition to the use of refined visual language in its execution with particular industry relevancy for which their project is intended. Students draw upon the philosophical, practical, methodological, theoretical and technical tools they have gathered over the duration of the degree to complete a successful project. Students are mentored through this research project by an industry supervisor with complementary practice-based research expertise. Projects must pertain to the field of software engineering and in particular to their specialisation. Students are required to work independently or as part of a collaborative team in order to conduct research, analyse and define project parameters and deliver innovative solutions.

This subject builds upon Technology – Work Integrated Learning enabling students to further develop and apply strategic processes, creative tools & research for innovation in the field of software engineering. It extends the opportunity to pursue the significant project in a professional environment in an area related to their specialisation enabling students to develop skills that enhance their prospects of gaining meaningful employment and build their career for the future.

They continue with the same option as chosen previously:

  • Option 1: Industry Placement Students are offered the opportunity to work within a technology company as an intern or volunteer at a technology non-profit organisation. It encourages students to build long-term relationships with the tech industry and provides an opportunity for them to work with and learn from people who may end up becoming colleagues, managers or mentors. It also provides a context in which to enhance their communication skills and work collaboratively in a professional arena. Students will undertake a series of industry-led tasks that are relevant to their field of study in order to understand the key concepts of working in and managing a professional technology team with emphasis placed on the operation of the environment.

  • Option 2: Industry Live Brief Industry live brief, also known as an industry project engages students in an activity where the parameters of success are set by the client. Academic staff and industry provide supervision for students, while industry provides, mentorship in addition. Numerous technology firms have ideas and opportunities they would like to explore and prototype; this is where students or student teams connect with industry to achieve scale with minimal risk. An understanding of research methodologies appropriate to professional practice and the documentation of personal creative investigation is explored. Students also further investigate and examine entrepreneurial and commercial opportunities through collaborative work practice. The subject fosters a cross-specialisation perspective and draws on both specialised and common software engineering practices. Students are required to work both independently and as part of a collaborative team that includes industry representatives to conduct research, analyse and define project parameters and deliver innovative solutions that expand the notion of an industry live brief.

  • Option 3: Capstone Students execute, finalise and present their self-initiated project exhibiting a sophisticated understanding of software engineering, whilst addressing the university ethos. Central to the project will be evidence of critical analysis, reflexive and reflective practice and social engagement, in addition to the use of refined visual language in its execution with particular industry relevancy for which their project is intended. Students draw upon the philosophical, practical, methodological, theoretical and technical tools they have gathered over the duration of the degree to complete a successful project. Students are mentored through this research project by an industry supervisor with complementary practice-based research expertise. Projects must pertain to the field of software engineering and in particular to their specialisation. Students are required to work independently or as part of a collaborative team in order to conduct research, analyse and define project parameters and deliver innovative solutions.

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