Bachelor of Data Science

Rmit's bachelor of data science will develop skills in data analytics, statistics, computer science, machine learning, programming, mathematics, and data wrangling that will enable you to be central to business decision-making, corporate strategy and government planning. 

Overview

• Build in-demand skills, choose your area of study and follow your passion in the emerging and expansive field of data science.
• You will gain strong problem-solving skills, and learn how to effectively communicate your work to technical and non-technical audiences, work independently or as a team, and factor in relevant standards, ethical and legal considerations to your projects.
• Using cutting-edge technologies, you will learn how to analyse and manage large amounts of data from various sources and evaluate their insights and solutions. You will gain hands-on experience using Python and R programming languages. 
• Personalise your degree to suit your career aspirations, selecting from a wide range of majors and minors. Major in advanced data science, cyber security or enterprise systems. Specialise in AI, data analysis, cloud computing, mixed reality, software development and blockchain.  
• Gain industry experience and connections while you study through work integrated learning experiences. Opportunities include capstone projects, case studies and programming studios.

Why study data science at RMIT?

• Learn from industry leaders- Engage with leading academics, teachers, guest lecturers and subject matter experts with strong industry connections.
• Enhance employability- Gain in-demand skills and experience through work integrated learning opportunities, capstone projects, and programming bootcamps and studios.
• Hone your skills- Develop your ability to analyse and manage big data from various sources, evaluating their insights and solutions.

How you will learn

Learning and teaching

• The teaching approach in this degree is designed to foster your development as an independent learner so you will be able to extend your capabilities once you graduate.
• In your first year, you will complete innovative data science bootcamp and studio subjects in RMIT's Bootcamp2Studio model, developing a comprehensive knowledge of programming and gaining career-ready experience.
• You will learn through a broad mix of study modes, including lectures, seminars, tutorials, workshops and practical and laboratory classes, using face-to-face, online, and other flexible delivery mechanisms.

Assessment methods

• Assessment will be through a combination of exams, tests, quizzes, essays, reports, assignments, projects, presentations, and laboratory assessments.

Learning at RMIT

• The types of classes you have will depend on the course you’re studying. Classes are offered in various formats designed to provide meaningful engagement with staff, industry and peers and provide for access and use of spaces where learning can be applied and active, including an array of specialised equipment.
• Most RMIT courses do not include passive large-scale classes such as lectures, instead the content traditionally provided in lectures is made available online. This may be in the form of readings, videos or other on-demand learning materials. This content will also support the basis of interactive learning that takes place in on-campus classes.

Bootcamp2studio model

• In the Bootcamp2Studio model, you will undertake up to six weeks of intensive, focused learning across a programming bootcamp.
• Next, you'll spend nine weeks learning in a studio model. Here, you'll explore your project more deeply, working both in groups and independently to solve real-world challenges.
• Through this hybrid form of teaching, you'll build transferable skills in problem solving and teamwork, learn to adapt to new projects, technologies and settings quickly, and be exposed to professional practice and standards that prepare you for your future workplace.

Industry connections

• The School of Computing Technologies has strong links with the data science profession and related areas of business, governement and industry, in Australia and internationally.
• Data science experts contributed to the initial development of this data science course and continue to provide input to improve the degree. Their involvement ensures the degree remains relevant to your needs as a graduate and to the needs of employers.
• Learn and be inspired by academics with strong research backgrounds and links to industry, as well as sessional teachers, guest lecturers and industry practitioners.
• Engage with industry through work integrated learning (WIL) experiences, which will enable you to learn, apply and demonstrate your knowledge and skills in a workplace setting (real or simulated) and receive feedback from data scientists working in industry.
• WIL opportunities include completing an industry capstone project, where you will apply your data science knowledge to plan and execute a substantial research-based or industry-sponsored project. You will also complete a case studies in data science subject where you will receive feedback from data scientists working in industry.

Year 1

• In your first year, you will complete five core data science subjects to give you the foundation that you need to succeed in your chosen career path. The subjects include, mathematics for computing, artificial intelligence, data science, programming and cyber security.
• You will also complete two innovative programming bootcamp and studio subjects, which will allow you to develop your programming skills through practical, project-based work. 

Year 2

• After you have completed your first year, the direction you take is in your hands as you choose which majors, minors and subjects you want to undertake. You can choose one or more minors from diverse data science fields of study, or just focus on the individual subjects and electives that interest you most.

Majors include:

• Advanced Data Science
• Cyber Security
• Enterprise System Development

Minors include: 

• Artificial Intelligence and Machine Learning
• Blockchain Technologies
• Cloud Computing
• Creative Computing
• Cyber Assurance
• Enterprise Systems Development
• Data Analysis
• Bioinformatics

In your second year, you will complete a data science case study which will teach you the end-to-end process of approaching a data science problem. 

In your third year, you will complete a capstone project with industry, providing you with hands-on, practical experience analysing data in a business setting.

You will also choose two subjects, with options including one from machine learning or data mining, and the other from STEM for sustainable development or cyber-physical-biological systems.

Career

Data scientists are some of the most highly sought after and highly paid professionals in the world. 

• As a graduate of this data science degree, you will have the theoretical and practical knowledge needed to pursue an interesting and flexible data science career in a range of data-driven industries and organisations.

Jobs in this in-demand field are vast and may include:

• Analytics specialist
• Business intelligence developer
• Data analyst 
• Data architect
• Data engineer 
• Data miner
• Data scientist
• Machine learning engineer
• Programmer
• Research data scientist 
• Web analyst