KOI is regulated by the Tertiary Education Quality and Standards Agency (TEQSA) and operates within the requirements of the Australian Qualifications Framework (AQF) and the Higher Education Standards Framework (Threshold Standards). The Bachelor of Data Science and Artificial Intelligence has been self-accredited by KOI under its LSAA, in accordance with the
relevant Australian higher education standards.

The subjects in the boxes must be studied in the order they are presented as they provide pre-requisite knowledge for other subjects. The remaining subjects (core and elective) have a recommended trimester provided pre-requisites have been completed.
Students may choose any elective subjects from the list following the Course Overview, provided the subject is offered in the trimester they wish to study it and they have met the relevant pre-requisites.
The Bachelor of Data Science and Artificial Intelligence course aims to develop professionals capable of extracting, analysing, and applying data driven insights to solve real-world problems. It offers a strong foundation in data science principles, statistical modelling, machine learning, artificial intelligence, and ethical data practices—core competencies essential in today’s data-driven economy. The course equips graduates with cutting-edge analytical, computational, and problem-solving skills that are in high demand worldwide. Through a curriculum grounded in innovation, ethical practice, and real- world application, students develop the confidence and capability to contribute meaningfully in diverse international industries. The program’s emphasis on practical learning, collaboration, and adaptability ensures that graduates are not only technically proficient but also prepared to thrive as responsible and globally minded data professionals. Graduates of the Bachelor of Data Science and Artificial Intelligence will possess the knowledge, skills, and professional capabilities to operate effectively in a data-driven world. They will be able to collect, manage, analyse, and interpret complex data to generate actionable insights and support evidence-based decision-making across a range of sectors, including business, health, education, finance, and technology.
Graduates will have a range of career opportunities across data science, analytics, and artificial intelligence. Potential career options include Data Scientist, Data Analyst, Data Engineer, Machine Learning Engineer, Business Intelligence Analyst, Statistician, Data Consultant, AI Researcher/Research Scientist, AI Product Manager, AI Consultant, and AI Engineer.
The Bachelor of Data Science and Artificial Intelligence course requires students to complete 20 Core subjects (80 credit points) and 4 Elective subjects (16 credit points). The curriculum includes subjects such as Programming in Python and R, Database Systems, Data Analytics, Machine Learning, Advanced Machine Learning, and Artificial Intelligence, together with specialised electives in Data Science, Artificial Intelligence, and Information Technology.
The curriculum integrates theoretical foundations with practical, industry-relevant skills aligned with contemporary developments in data science and artificial intelligence. Students are encouraged to pursue industry-recognised certifications from providers such as Google, AWS, Microsoft Azure, and IBM, while industry guest lectures, faculty expertise, and real-world Capstone Projects throughout the course provide exposure to current industry trends and workforce needs.
Course Learning Outcomes
Delivery Mode
Subject Credit Points
Exit Pathways
POSSIBLE CAREER PATHS
Graduates of the Bachelor of Data Science and Artificial Intelligence find employment in a varied range of industries and positions. Some of the possible career options are as a Data Scientist, Data Analyst, Data Engineer, Machine Learning Engineer, Business Intelligence Analyst, AI Consultant, AI Engineer, etc.
APPROACH TO LIFE-LONG LEARNING AND FURTHER STUDY
Lifelong learning and further study are essential for graduates to stay competitive and advance their careers. KOI students are equipped with skills for life-long learning and encouraged to recognise that learning is a continual process which extends beyond completion of their degree.
Graduates need to be prepared for rapidly transforming job markets due to the emergence of new technologies and market trends. They should prioritise learning by seeking out options that work best for them. Professional development opportunities abound in both online and in-person formats. They include attending seminars and workshops, completing short courses, reading books and articles, networking and many others. By taking the initiative to stay informed and constantly expanding their skill sets, graduates will be better equipped to find both personal satisfaction and success in their chosen careers.
PATHWAY TO FURTHER STUDIES
Graduates of the Bachelor of Data Science and Artificial Intelligence are eligible to apply for admission into postgraduate qualifications in Australia and overseas. Graduates may also apply to study the Master of Information Technology or Master of Information Systems at KOI, subject to the applicable admission requirements.
STUDENT PROFILE
The table in the pop-up window here gives an indication of the likely peer cohort for new students at KOI. It provides data on students that commenced Bachelor of Data Science and Artificial Intelligence study and passed the census date in the most relevant recent intake period for which data are available, including those admitted through all offer rounds, across all Australian campuses, and international students studying in Australia.
ATAR PROFILE
The table in the pop-up window here gives ATAR profile for those offered places wholly or partly on the basis of ATAR in Trimester 1, 2026
ADMISSION REQUIREMENTS
General admission criteria apply to the course.
COURSE CONDITIONS
To be permitted to enrol in this course:
KOI will admit students in Bachelor of Data Science and Artificial Intelligence who have an NSW Higher School Certificate or equivalent showing satisfactory completion of Year 12 at a standard equivalent to ATAR 70.00 or above.
| BUS100 | Professional Communication Skills |
| ICT105 | AI Governance |
| ICT102 | Introduction to Programming |
| ICT106 | Data Communications and Networks |
| ICT108 | Introduction to Data Analytics and Visualisation (ICT102) |
| ICT303 | Professional Ethics in Computing (Completion of 12 CPs) |
| ICT200 | Database Design and Development |
| BUS105 | Business Statistics |
| ICT208 | Data Structure and Algorithms (ICT102) |
| ICT204 | Project Management (Completion of 20 CPs) |
| ICT101 | Discrete Mathematics for IT |
| ICT310 | Data Integration and Wrangling (ICT102 and ICT200) |
| ICT312 | Big Data Analytics (ICT108) |
| ICT371 | Artificial Intelligence (ICT102 and 40 CPs) |
| ICT314 | Machine Learning (ICT108 and BUS105, Co-req: ICT208) |
| ICT308 | Decision Making Methods (BUS105 and ICT101) |
| ICT316 | Generative AI and Applications in Data Science (ICT314) |
| ICT318 | Computational Intelligence (ICT314 and ICT371) |
| General Elective / Job Ready Program | |
| Spec-Elective |
| ICT300 | Capstone Project (64 CPs) (ICT371, ICT314 and ICT316) |
| ICT322 | Deep Learning (ICT102 and ICT314) |
| General Elective / Job Ready Program | |
| Spec-Elective |
Note: There is only one Job Ready Program, which students can undertake in either the second-last or final trimester.
(Additional charges may apply, and fees may vary)
Electives: Provided that pre-requisites have been met, and the subject is offered in the trimester, students may choose any electives from the list below. (Pre-requisite shown in brackets.)
Information Technology Electives
ICT205 Cyber Security (ICT106)
ICT373 Cloud Computing (ICT106)
ICT203 Human Computer Interaction (6 subjects completed)
Data Science and Artificial Intelligence Electives
ICT320 Advance Machine Learning (ICT314, co-req: ICT310 and ICT308)
ICT324 Natural Language Processing
Accounting Electives
ACC100 Introduction to Accounting
ACC101 Introduction to Financial Accounting (ACC100)
ACC200 Introduction to Management Accounting (ACC100)
Business Electives
BUS101 Introduction to Business Law
BUS104 Introduction to Marketing
BUS302 Entrepreneurship (BUS104)
Finance Electives
FIN200 Corporate Financial Management
FIN201 Investment Management (FIN200)
FIN203 Banking and Finance (FIN200)