Bachelor of Science (Advanced Mathematics)(Honours)/Science (Computer Science)

5 Years On Campus Bachelors Program

University of New South Wales

Program Overview

The Bachelor of Science (Advanced Mathematics) (Honours) / Science (Computer Science) at the University of New South Wales (UNSW) is designed for high-achieving students who are passionate about solving complex problems at the intersection of mathematics and computing. This degree suits analytical thinkers who enjoy challenges in logic, data, and technology, combining advanced mathematical theory with cutting-edge computer science practice.


Curriculum Structure

Year 1:
Students begin by developing a solid foundation in both mathematics and computing. Core courses such as Mathematical Computing, Foundations of Computer Science, and Calculus 1A introduce problem-solving techniques, programming fundamentals, and key mathematical principles that underpin advanced study. This year focuses on building technical confidence and logical reasoning skills essential for later years.

Year 2:
The second year deepens students’ expertise through courses like Linear Algebra, Data Structures and Algorithms, and Computational Mathematics. Here, they learn how to analyse data, design efficient algorithms, and apply mathematical tools to solve real-world computational challenges. The integration of theory with applied computing strengthens analytical precision and technical fluency.

Year 3:
Students engage with advanced topics such as Probability and Stochastic Processes, Artificial Intelligence, and Mathematical Modelling. This stage encourages creative problem-solving, introducing complex systems, predictive modelling, and intelligent computation. Students also begin exploring areas of specialisation that align with their career interests or research goals.

Year 4 (Honours):
The final year is research-intensive, culminating in an Honours thesis that allows students to conduct original research under academic supervision. Advanced electives in Computational Data Science, Optimisation Theory, or Machine Learning further refine their expertise, preparing them for leadership roles in research, technology, or academia.


Focus Areas:
Advanced mathematics, computational theory, data science, artificial intelligence, algorithms, optimisation, mathematical modelling

Learning Outcomes:
Students graduate with advanced analytical, programming, and research skills; the ability to design complex algorithms; and the expertise to apply mathematical reasoning to technological innovation.

Professional Alignment (Accreditation):
Accredited by the Australian Computer Society (ACS), ensuring alignment with professional standards in computing and IT.

Reputation (Employability Rankings):
UNSW ranks among the top 20 universities worldwide for Computer Science and Mathematics (QS World University Rankings by Subject 2025), and is recognised as one of Australia’s most employable universities for STEM graduates.

Experiential Learning (Research, Projects, Internships etc.)

If you’re thinking about studying the Bachelor of Science (Advanced Mathematics) (Honours) / Science (Computer Science) at the University of New South Wales (UNSW), you’re looking at a degree that’s all about doing, not just studying. This program takes you beyond theory — you’ll explore deep mathematical concepts while also developing practical skills in computing, algorithm design, system development, data analysis and research. With world-class facilities, strong industry connections and research-driven teaching, you’ll gain hands-on experience that prepares you for real-world careers from day one.


Here’s how you’ll gain experiential learning through this program:

  • Hands-on facilities: You’ll have access to UNSW Science’s state-of-the-art labs, simulators and research centres. These spaces let you put classroom theory into practice, experimenting with real data, models and systems.

  • Honours research year: Your final year includes an original research project supervised by leading academics. It’s your chance to dive into a topic that interests you, contribute new insights, and experience what real scientific research is like.

  • Work-Integrated Learning (WIL): UNSW offers placements, industry projects and research-based internships where you can work directly with professionals in science or tech, earning credit while gaining valuable workplace experience.

  • Cutting-edge computer science majors: You can specialise in areas like Artificial Intelligence, Security Engineering or Embedded Systems — developing practical skills in programming, algorithm design and system development through applied coursework.

  • Blended learning approach: Your studies will combine pure and applied mathematics (in areas like applied maths, pure maths or advanced statistics) with computer science, helping you build both analytical precision and technical expertise.

  • Strong industry connections: With over 400 industry and research partners, UNSW gives you direct access to networking opportunities, internships and collaborations that help you build a professional foundation before you graduate.

  • Comprehensive academic support: You’ll make use of UNSW’s world-class library, research institutes and computing centres — all part of the Science faculty’s infrastructure that supports your projects, coding and data analysis.

  • Collaborative learning environment: You’ll work in team-based tutorials and group projects that mirror professional settings, sharpening your problem-solving, communication and teamwork skills alongside your technical knowledge.


In short: this degree is about designing, building, researching and collaborating. With modern facilities, innovative teaching and real-world learning opportunities, you’ll graduate ready to take on complex challenges — whether in advanced tech roles, research or postgraduate study.

Progression & Future Opportunities

Progression & Future Opportunities:
Graduates of the Bachelor of Science (Advanced Mathematics) (Honours) / Science (Computer Science) at the University of New South Wales (UNSW) are highly sought after for their strong analytical thinking, computational expertise, and problem-solving ability. Many go on to excel in roles across technology, research, finance, and data-driven industries. Typical career paths include Data Scientist, Software Engineer, Quantitative Analyst, and Machine Learning Specialist.

UNSW supports students in translating their skills into meaningful careers through a range of dedicated services and industry connections:

  • UNSW Employability Service helps students build professional experience through internships, mentoring, and networking events with leading employers.

  • Graduates benefit from UNSW’s strong industry partnerships with organisations such as Microsoft, Atlassian, Deloitte, and CSIRO, giving students access to real-world projects and career pathways.

  • According to the UNSW Graduate Outcomes Survey, over 90% of science and technology graduates find full-time employment or pursue further study within four months of graduating.

  • UNSW ranks 1st in Australia for graduate employability (QS Graduate Employability Rankings 2024), reflecting the long-term value and global recognition of its degrees.

  • This double degree’s accredited and research-led curriculum ensures that graduates meet international professional standards and are prepared for emerging fields in AI, data analytics, and computational modelling.

Further Academic Progression:
After completing this program, students can progress into advanced research or professional study. Many pursue a Master of Data Science, Master of Information Technology, or a PhD in Computer Science, Applied Mathematics, or Artificial Intelligence at UNSW or other leading global universities. This pathway positions graduates to contribute to innovation, research, and leadership in technology and science sectors.

Program Key Stats

$58,500
$7,500
$ 215
Rolling


No
Yes

Eligibility Criteria

AAA
3.3
33
81

N/A
N/A
6.5
90

Additional Information & Requirements

Career Options

  • Software Developer
  • Data Analyst
  • Web Developer
  • Systems Analyst
  • Cybersecurity Specialist
  • Database Administrator
  • AI Engineer
  • Cloud Architect
  • IT Consultant
  • Network Engineer
  • Machine Learning Engineer
  • Game Developer
  • DevOps Engineer
  • Research Scientist
  • Mobile App Developer

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