Master of Data Science and Artificial Intelligence
Information and Communication Technologies (ICTs) · School of Computing and Engineering
Advanced data science, machine learning and responsible AI with end-to-end model delivery and industry projects.
Platform curated- Duration
- 2 years
- Full time · On campus
- Qualification
- Master Degree (Coursework)
- AQF 9
- Campus
- Sydney
- NSW
- Course code
- Program ACV-MDSAI
Campus images supplied directly by the institution.
Course overview
Students progress through statistical modelling, data engineering and machine learning into deep learning, natural language processing and responsible deployment. A two-part capstone uses a substantial real-world dataset.
Entry requirements
Requirements are recorded per intake year and per audience. Meeting them does not guarantee an offer.
Hold a recognised bachelor degree at the listed GPA-equivalent threshold and meet the course English requirement. All values are illustrative demo data.
Academic qualifications
Values are shown exactly as the institution publishes them.
Prior degree GPA
Recognised bachelor degree; GPA 2.75 / 4.0 or equivalent
68.75%
English language
Band minimums apply in addition to the overall score.
- IELTS AcademicOverall 6.5L 6 · R 6 · W 6 · S 6
- PTE AcademicOverall 58L 50 · R 50 · W 50 · S 50
- TOEFL iBTOverall 82L 13 · R 13 · W 21 · S 18
Additional requirements
Course-specific preparation
A recognised bachelor degree is required. Prior statistics or programming is recommended; foundation options are built into the study plan.
Course structure
What it takes to complete this qualification.
Total credit
160credit points
Total subjects
16
Core studies
Core10 subjectsRequired disciplinary and professional foundations.
Specialisation and electives
Specialisation4 subjectsChoice subjects used to shape the student's academic and career direction.
Applied project
Capstone2 subjectsData pipelines, reproducible experiments, model deployment and a two-part industry data capstone.
Intakes and tuition
Tuition is recorded per intake with the institution's own basis. Superseded rows are kept so fee changes stay visible.
| Intake | Campus | Starts | Applications close | Tuition | For |
|---|---|---|---|---|---|
| 2027 · Semester 1 | Achieva City Campus | 1 March 2027 | 31 January 2027 | $44,200per year | International students |
Where it is taught
Achieva City Campus
PrimaryLevel 10, 580 George Street, Sydney NSW 2000, Australia, Sydney, NSW
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Course FAQs
Questions the institution answers about this course.
What practical learning is included?
Data pipelines, reproducible experiments, model deployment and a two-part industry data capstone. This is an illustrative course description for the product demo.
References
Official course page, institution website and the sources behind this profile.