C10474v1 Bachelor of Artificial Intelligence
Award(s): Bachelor of Artificial Intelligence (BAI)UAC code: 603236 (Autumn session, Spring session, Spring session)
CRICOS code: 110746J
Commonwealth supported place?: Yes
Load credit points: 144
Course EFTSL: 3
Location: City campus
Overview
Course aims
Career options
Innovation and Transdisciplinary program
Course intended learning outcomes
Admission requirements
Pathway course
Inherent (essential) requirements
Assumed knowledge
External articulation
Recognition of prior learning
Course duration and attendance
Course structure
Course completion requirements
Course diagram
Course program
Levels of award
Honours
Transfer between UTS courses
Professional recognition
Other information
Overview
The Bachelor of Artificial Intelligence is designed to meet the need for specialised industry professionals to help organisations and society make sense of the abundance of data collected every second and build autonomous solutions for a variety of applications, such as self-driving cars, facial recognition, personalised learning or voice assistants. There is a strong industry demand for artificial intelligence professionals with sound technical capabilities and a good understanding of the challenges and opportunities in this rapidly evolving field.
This course provides students with the opportunity to gain the skills and knowledge required to meet the demands of this exciting field. Students in the course engage in practical, hands-on learning using technologies to formulate and scope an AI problem, and design, develop, verify and validate solutions for defined problems. The course covers a broad range of current and emerging areas of artificial intelligence, such as deep learning, reinforcement learning, image processing and natural language processing.
Course aims
The Bachelor of Artificial Intelligence is a three-year undergraduate-entry degree leading to eligibility to start a career as an artificial intelligence professional.
Students participate in a variety of innovative, inquiry-based, collaborative learning activities, which enable them to identify, analyse and manage challenges in various aspects of Artificial Intelligence. They learn how to formulate and scope an AI problem, and design, develop, verify and validate solutions for defined problems. Classes use state-of-the-art software and tools to integrate theoretical and practical concepts in AI. Students have access to case studies of real-world AI problems, that prepare them for a range of career opportunities in industry and business world. Learning is underpinned by a solid foundation in mathematics, statistics, information technology and software development, preparing them to work in a variety of IT roles that draw on both their broad IT knowledge and AI specialist skillset.
Exposure to various specialized areas in AI, such as deep learning, reinforcement learning, image processing and natural language processing, enable students to reflect on the need and importance of AI, build in-depth knowledge and ability to apply Artificial Intelligence to solve real-world problems. With educational opportunities to develop critical thinking and problem-solving skills, they are able to apply these professional skills in the workplace, and offer original solutions to challenges that current industries are facing in the era of big-data, cloud, and automation. Students also develop strong interpersonal skills and a capacity for teamwork.
As they study, students are able to design, build and evaluate AI solutions for applications such as autonomous cars, facial recognition, personalised learning, or voice assistants. Career options may include working as an artificial intelligence expert, artificial intelligence consultant, AI Specialist, machine learning engineer, data scientist, business analyst, software developer or data analyst.
Career options
Career options include AI Analyst, Machine Learning Engineer, AI Specialist, Computer Vision Engineer, Natural Language Processing Engineer.
Innovation and Transdisciplinary program
Transdisciplinarity and Innovation at UTSAll UTS students have the opportunity to develop distinctive capabilities around transdisciplinary thinking and innovation through the TD School. Transdisciplinary education at UTS brings together great minds from different disciplines to explore ideas that improve the way we live and work in the world. These offerings are unique to UTS and directly translate to many existing and emerging roles and careers.
Diploma in InnovationThe Diploma in Innovation (C20060) teaches innovation, supports personal transformation and provides the hard skills needed to support the inventors and inventions of the future. Students come out of the Diploma in Innovation, with the hard skills to create and support sectoral and societal transformation. Graduates are able to fluently integrate ideas, across professional disciplines and are inventors of the future.
All UTS undergraduate students (with the exception of students concurrently enrolled in the Bachelor of Creative Intelligence and Innovation) can apply for the Diploma in Innovation upon admission in their chosen undergraduate degree. It is a complete degree program that runs in parallel to any undergraduate degree. The course is offered on a three-year, part-time basis, with subjects running in 3-week long intensive blocks in July, December and February sessions. More information including a link to apply is available at https://dipinn.uts.edu.au.
Transdisciplinary electives programTransdisciplinary electives broaden students' horizons and supercharge their problem-solving skills, helping them to learn outside, beyond and across their degrees. Students enrolled in an undergraduate course that includes electives can choose to take a transdisciplinary subject (with the exception of students concurrently enrolled in the Bachelor of Creative Intelligence and Innovation). More information about the TD Electives program is available here.
Course intended learning outcomes
| A.1 | Bachelor of Artificial Intelligence graduates, will have knowledge of Indigenous Australian contexts to apply professional capabilities to work with and for Indigenous Australians across artificial intelligence projects and industry. |
| B.1 | Bachelor of Artificial Intelligence graduates are able to identify a broad range of organisational stakeholders on Artificial Intelligence issues, and demonstrate ethical, personal, organisational, policy, social and environmental awareness on the impacts of Artificial Intelligence in diverse contexts. |
| C.1 | Bachelor of Artificial Intelligence graduates demonstrate autonomy and apply expert judgment in the design and evaluation of innovative Artificial Intelligence solutions to organisational, societal and global problems. |
| D.1 | Bachelor of Artificial Intelligence graduates demonstrate and apply fundamental knowledge in Artificial Intelligence and related fields of information technology, including technical skills in designing and implementing AI solutions incorporating current and emerging technologies. |
| E.1 | Bachelor of Artificial Intelligence graduates communicate professionally in a variety of ways to diverse audiences and collaborate across functional, hierarchical and professional boundaries, within and across organisations, in local and global contexts. |
| F.1 | Bachelor of Artificial Intelligence graduates work and thrive in the world of constant technological change by being self-reflective, thoughtful and life-long learning professionals, dedicated to seeking feedback, applying well-developed judgement, pursuing self-development and making a positive difference in organisations and the wider society. |
Admission requirements
Applicants must have completed an Australian Year 12 qualification, Australian Qualifications Framework Diploma, or equivalent Australian or overseas qualification at the required level.
The English proficiency requirement for international students or local applicants with international qualifications is: Academic IELTS: 6.5 overall with a writing score of 6.0; or TOEFL: paper based: 550-583 overall with TWE of 4.5, internet based: 79-93 overall with a writing score of 21; or AE5: Pass; or PTE: 58-64 with a writing score of 50; or C1A/C2P: 176-184 with a writing score of 169.
Eligibility for admission does not guarantee offer of a place.
International students
Visa requirement: To obtain a student visa to study in Australia, international students must enrol full time and on campus. Australian student visa regulations also require international students studying on student visas to complete the course within the standard full-time duration. Students can extend their courses only in exceptional circumstances.
Pathway course
International applicants who complete the UTS College Diploma of Information Technology with no more than two subject failures are guaranteed admission to the Bachelor of Artificial Intelligence with up to 48 credit points of recognition of prior learning.
Inherent (essential) requirements
Inherent (essential) requirements are academic and non-academic requirements that are essential to the successful completion of a course.
Prospective and current students should carefully read the Inherent (Essential) Requirements Statement below and consider whether they might experience challenges in successfully completing this course. This Statement should be read in conjunction with the UTS Student Rules.
Prospective or current student concerned about their ability to meet these requirements should discuss their concerns with the Academic Liaison Officer in their faculty or school and/or UTS Accessibility Service on 9514 1177 or at accessibility@uts.edu.au.
UTS will make reasonable adjustments to teaching and learning, assessment, professional experiences, course related work experience and other course activities to facilitate maximum participation by students with disabilities, carer responsibilities, and religious or cultural obligations in their courses.
For course specific information see the Faculty of Engineering & Information Technology Inherent (Essential) Requirements Statement.
Assumed knowledge
HSC Mathematics Advanced and any two units of English. Mathematics Extension 1 and English Advanced are recommended.
External articulation
Students who have completed a relevant diploma at TAFE NSW may be eligible for at least 24 credit points of recognition of prior learning.
Recognition of prior learning
Students who have completed equivalent subjects at a recognised tertiary education institution may be eligible for recognition of prior learning (RPL) if the subjects completed are deemed by the Faculty to be equivalent to subjects in the course. Established agreements for RPL with external tertiary institutions are outlined in the Recognition of prior learning tool.
To be considered for recognition of prior learning, subjects must normally have been completed no more than ten years prior to the commencement of this course. Limits apply to the number of credit points of RPL that can be granted.
Course duration and attendance
The course is completed in three years of full-time study. Students may undertake an additional year with the Diploma in Information Technology Professional Practice (C20056).
Course structure
Students are required to complete 144 credit points, comprising:
- Information Technology Core (48 credit points)
- AI core (54 credit points)
- AI choice of (18 credit points)
- Electives or a sub-major choice of (24 credit points)
Course completion requirements
| STM90651 Core subjects (Information Technology) | 48cp | |
| STM91743 Artificial Intelligence core | 54cp | |
| CBK92166 Artificial Intelligence options | 18cp | |
| CBK90783 Electives/Sub-major | 24cp | |
| Total | 144cp |
Course diagram
Course program
The program below shows a suggested sequence of subjects for a full-time student. It is intended as a guide only and does not take into account such factors as recognition of prior learning, changes in attendance mode and subject availability, or satisfactory academic progress. Students should consult the Timetable Planner to confirm the availability of subjects in the current academic year.
| Autumn commencing, full time | ||
| Year 1 | ||
| Autumn session | ||
| 33130 Mathematics 1 | 6cp | |
| 31268 Web Systems | 6cp | |
| 37181 Discrete Mathematics | 6cp | |
| Select 6 credit points from the following: | 6cp | |
| 48023 Programming Fundamentals | 6cp | |
| 41039 Programming 1 | 6cp | |
| Spring session | ||
| 31265 Communication for IT Professionals | 6cp | |
| 31271 Database Fundamentals | 6cp | |
| 31250 Introduction to Data Analytics | 6cp | |
| 31266 Introduction to Information Systems | 6cp | |
| Year 2 | ||
| Autumn session | ||
| 33230 Mathematics 2 | 6cp | |
| 41092 Network Fundamentals | 6cp | |
| 48024 Programming 2 | 6cp | |
| 31269 Business Requirements Modelling | 6cp | |
| Spring session | ||
| 31005 Machine Learning | 6cp | |
| 41040 Introduction to Artificial Intelligence | 6cp | |
| 57304 The Ethics of Data and AI | 6cp | |
| Select 6 credit points from the following: | 6cp | |
| CBK92069 Transdisciplinary Electives | 6cp | |
| Year 3 | ||
| Autumn session | ||
| 41004 AI/Analytics Capstone Project | 6cp | |
| 31272 Project Management and the Professional | 6cp | |
| Select 6 credit points from the following: | 6cp | |
| 41043 Natural Language Processing | 6cp | |
| 42028 Deep Learning and Convolutional Neural Network | 6cp | |
| 43007 Advanced Artificial Intelligence | 6cp | |
| 43023 Emerging Topics in Artificial Intelligence | 6cp | |
| 43024 Introduction to Computational Intelligence | 6cp | |
| Select 6 credit points from the following: | 6cp | |
| CBK92186 Electives | 18cp | |
| Spring session | ||
| Select 12 credit points from the following: | 12cp | |
| 31243 AI/Analytics Capstone Project B | 6cp | |
| 31256 Image Processing and Pattern Recognition | 6cp | |
| 32146 Data Visualisation and Visual Analytics | 6cp | |
| 41080 Theory of Computing Science | 6cp | |
| 43008 Reinforcement Learning | 6cp | |
| 48033 Internet of Things | 6cp | |
| Select 12 credit points from the following: | 12cp | |
| CBK92186 Electives | 18cp | |
| Spring commencing, full time | ||
| Year 1 | ||
| Spring session | ||
| 33130 Mathematics 1 | 6cp | |
| 31266 Introduction to Information Systems | 6cp | |
| 31265 Communication for IT Professionals | 6cp | |
| Select 6 credit points from the following: | 6cp | |
| 48023 Programming Fundamentals | 6cp | |
| 41039 Programming 1 | 6cp | |
| Year 2 | ||
| Autumn session | ||
| 33230 Mathematics 2 | 6cp | |
| 31250 Introduction to Data Analytics | 6cp | |
| 48024 Programming 2 | 6cp | |
| 37181 Discrete Mathematics | 6cp | |
| Spring session | ||
| 41040 Introduction to Artificial Intelligence | 6cp | |
| 31005 Machine Learning | 6cp | |
| 31271 Database Fundamentals | 6cp | |
| 31269 Business Requirements Modelling | 6cp | |
| Year 3 | ||
| Autumn session | ||
| 57304 The Ethics of Data and AI | 6cp | |
| 31268 Web Systems | 6cp | |
| 41092 Network Fundamentals | 6cp | |
| Select 6 credit points from the following: | 6cp | |
| CBK92069 Transdisciplinary Electives | 6cp | |
| Spring session | ||
| 31272 Project Management and the Professional | 6cp | |
| Select 12 credit points from the following: | 12cp | |
| 31243 AI/Analytics Capstone Project B | 6cp | |
| 31256 Image Processing and Pattern Recognition | 6cp | |
| 32146 Data Visualisation and Visual Analytics | 6cp | |
| 41080 Theory of Computing Science | 6cp | |
| 43008 Reinforcement Learning | 6cp | |
| 48033 Internet of Things | 6cp | |
| Select 6 credit points from the following: | 6cp | |
| CBK92186 Electives | 18cp | |
| Year 4 | ||
| Autumn session | ||
| 41004 AI/Analytics Capstone Project | 6cp | |
| Select 6 credit points from the following: | 6cp | |
| 41043 Natural Language Processing | 6cp | |
| 42028 Deep Learning and Convolutional Neural Network | 6cp | |
| 43007 Advanced Artificial Intelligence | 6cp | |
| 43023 Emerging Topics in Artificial Intelligence | 6cp | |
| 43024 Introduction to Computational Intelligence | 6cp | |
| Select 12 credit points from the following: | 12cp | |
| CBK92186 Electives | 18cp | |
Levels of award
The Bachelor of Artificial Intelligence may be awarded with distinction, credit or pass.
Honours
Students interested in research and who excel in their studies are eligible to undertake one additional full-time year of study in the Bachelor of Information Technology (Honours) (C09019). The honours year is also available on a part-time basis over two years.
Transfer between UTS courses
Students in this course may transfer to the Bachelor of Artificial Intelligence Bachelor of International Studies (C10475).
Professional recognition
Graduates are eligible to apply for professional-level membership of the Australian Computer Society.
Other information
Further information is available from:
UTS Student Centre
telephone 1300 ask UTS (1300 275 887) or +61 2 9514 1222
Ask UTS