Master in Data Science

The University of Adelaide, established in 1874 and located in the city of Adelaide, serves a diverse student body of about 29,006, including more than 9,200 international students. The university offers a wide range of undergraduate and postgraduate options across research-led faculties and lists around 208 programs, making it a strong choice for students seeking rigorous academic training combined with practical learning.

Students at Adelaide benefit from research-active staff, industry partnerships and facilities designed to support innovation and employability. The university supports international entrants through admissions guidance, English-language preparation and orientation activities that connect students with peers, mentors and local communities. Campus services focus on academic skills, career planning and student wellbeing to ensure a successful transition into study and life in Australia.

Adelaide itself is known for a high quality of life, accessible cultural amenities and a reputation for safety and affordability among Australian cities. International students can explore internships, research collaborations and community engagement while enjoying a manageable urban environment. Scholarships and targeted support help make study more accessible and provide pathways to professional networks after graduation.

The Master in Data Science at the University of Adelaide is a master's degree for students who want to learn about data science. It takes one year to complete and is taught in English. The main advantage of this program is that it helps students develop skills in data science.

The curriculum includes core courses like Foundations of Computer Science, Mathematical Foundations of Data Science, and Data Taming. Students also learn about human and ethical factors in computer science, data literacy, and statistical machine learning. The program has hands-on components like an internship and a research project.

Graduates of this program can work as Data Scientists, Business Analysts, Data Engineers, Machine Learning Engineers, or Statisticians. They can work in industries like finance, healthcare, or technology for employers like banks, hospitals, or software companies.