Data science professionals are in high demand in today's data-driven world. Master of Data Science prepares graduates for a successful career in this exciting field.
Designed in collaboration with the School's industry partners, this degree gives students the knowledge, skills and hands-on experience to transition from university to the workplace. And with two early exit points along the way, they can be sure that every subject is contributing to their career.
Graduates have opportunities to work with the industry partners on real-world projects and take on an industry work placement. If their sights are set on a research career, they can choose to undertake a thesis in computer science or statistics.
Students will learn:
- Data science: Get practical experience with open-source software and platforms, including Python, R and Hadoop.
- Understand database fundamentals, programming languages such as Java and Python, and cloud-based services offered by Amazon, Google, IBM and Microsoft.
- Mathematics and statistics: Learn how to create complex models and use powerful tools for advanced analysis and problem-solving.
- Build skills using real data sets from industry partners and learn how to solve data challenges facing businesses and organizations.
- Project management: Learn how to manage large-scale IT projects and work in a team to develop a small-scale, industry-based system.
- Complementary skills in other disciplines: Boost your knowledge through electives in business, health sciences, artificial intelligence and cybersecurity.
Graduates could work across a range of industries, including business and finance, science, education, health, and sports.
- Data scientist: Understand complex data and leverage it to the advantage of businesses and organizations.
- Business analyst: Understand how businesses run and use data to solve problems and improve processes.
- Health analyst: Gather, analyze and verify healthcare information.
- Bioinformaticians: Develop methods of research and analysis for understanding and leveraging biological and genomic data.
- Machine learning engineer: Use your detailed understanding of machine learning, big data, cloud technology and mathematics to create effective machine learning solutions.
