S3003 Bachelor of Applied Data Science Advanced (Honours)

The course develops through theme studies in data challenges, techniques drawn from information technologies and mathematics, and applied studies. You will learn to apply the knowledge you gain in specialised information technology and mathematics studies to a series of projects. These will come together in the Honours research project unit in the fourth year of the course. You will also develop discipline specific skills in selected areas of study.

Part A. Data challenges 
These studies will develop your analytical skills and advance your ability to apply key information technology and mathematical concepts and methods. These skills will be elaborated through studio-based learning using authentic case studies sourced from industry partners, and with examples drawn from STEM areas, business, law, the humanities and social sciences. Working in small teams or as individuals, you will realise the application of information technology and mathematical knowledge through authentic projects. Through designed experiences, you will learn to integrate a broad range of skills including collaborative work practices, communication, leadership and entrepreneurship to make you ready to approach the professions of the future.

Part B. Techniques for data science 
Through this theme you will gain the technical foundation that underpins this program. You will acquire knowledge and skills in mathematics and the capacity to tackle challenging problems in a variety of situations. Through core data science studies, you will also attain the skills needed to effectively use, develop and manage complex data. These two areas are critical for tackling the diverse problems encountered in Part A of the course.

Part C. Applied studies 
These studies will provide the foundation required to advance cross-disciplinary analytical thought. You will undertake a sequence of study in a discipline. The selection of studies available will ensure you can explore new and diverse areas and develop core strengths in studies that relate to data applications. In addition to the disciplinary expertise, you will develop an appreciation for the culture of your selected discipline, the development of ideas in a given subject area, and the contexts in which this is applied. Data applications relating to these subjects can then be incorporated through the learning experiences across Parts A and D.

Part D. Advanced practice 
This is the culmination of the course. You will synthesise the knowledge acquired during the program in an individual research project. You will be able to apply your skills to a real life project sourced from a variety of sectors. In addition, you will acquire valuable research skills and be able to demonstrate your capacity for research with some level of independence. The project will be supported by research training and you will expand your knowledge of data science by gaining exposure to cutting edge techniques through an advanced unit in data science.

Part E. Free elective 

This will enable you to further develop your technical skills or extend your knowledge in your selected applied studies. Alternatively you can select units from across the university in which you are eligible to enrol.

Course progression map

The course progression map provides guidance on unit enrolment for each semester of study.

The course comprises 192 points of which 168 points are focussed on Applied Data Science.

The course develops through theme studies in: A. Data Challenges (36 points), B. Techniques for data science (72 points), C. Applied studies (24 points), D. Advanced Practice (36 points) and E. Free electives (24 points).

No more than 10 units (60 points) are to be completed at level 1 in the course.

In order to progress to the fourth year, you must normally complete 144 points comprising 132 points as indicated in parts A, B and C and 12 points from part E.  You must also achieve a minimum of a distinction average (70%) in 36 points of core level 3 units. If you do not meet the course requirements you will be awarded the Bachelor of Applied Data Science.

Units are 6 points unless otherwise stated.

Part A. Data challenges (36 points)

You complete:

• ADS1001 Data challenges 1 
• ADS1002 Data challenges 2
• ADS2001 Data challenges 3
• ADS2002 Data challenges 4
• ADS3001 Advanced data challenges (12 points)

Part B. Techniques for data science (72 points)

You complete

(i) Six Information Technology units (36 points) from the following:

• FIT1043 Introduction to data science and artificial intelligence
• FIT1045 Introduction to programming
• FIT2086 Modelling for data analysis
• FIT2094 Databases
• FIT3154 Advanced data analysis  
• FIT3181 Deep learning

and

(ii) Six Mathematical Science units (36 points) from the following:

• MAT1830 Discrete mathematics for computer science or MTH1020 Analysis of change*
• MTH1030 Techniques for modelling 
• MTH2019 Multivariate mathematics for data science
• MTH2051 Introduction to computational mathematics
• MTH3320 Computational linear algebra
• MTH3330 Optimisation and operations research

*If you have achieved a raw study score of at least 30 in VCE Special Mathematics units 3 and 4, you complete MAT1830 Discrete mathematics for computer science. All the other students complete MTH1020 Analysis of change. 

Part C. Applied studies (24 points)

You complete 24 points of complementary studies from a defined discipline area listed below. Normally, you complete:

• 2 units at level 1 (12 points)
• 2 units at level 2, 3 or 4 (12 points)

Applied and statistical mathematics

Option 1: You complete option 1 if you have achieved a raw study score of at least 30 in VCE Special Mathematics units 3 and 4.   

• MTH2132 The nature and beauty of mathematics
• MTH2222  Mathematics of uncertainty or MTH2225 Mathematics of uncertainty (advanced)
• MTH2232 Mathematical statistics
• MTH2032 Differential equations 

Option 2: You complete option 2 if you do not meet the Mathematics requirement for option 1.

You complete:

• MAT1830 Discrete mathematics for computer science
• MTH2132 The nature and beauty of mathematics

and two of:

• MTH2222 Mathematics of uncertainty or MTH2225 Mathematics of uncertainty (advanced)
• MTH2232 Mathematical statistics
• MTH2032 Differential equations 

Astronomy

No more than one of

• ASP1010 Earth to cosmos: introductory astronomy
• ASP1022 Life in the universe: astrobiology

And one of

• PHS1011 Classical physics and relativity
• PHS1001 Foundation physics
• PHS1002 Physics for engineering

And

• ASP2011 Astronomy
• ASP2062 Introduction to astrophysics

Biological science and genetics

• BIO1011 Blueprints for life 
• BIO1022 Life on earth or BIO1042 Life in the environment 

One of:

• BIO2011 Ecology and biodiversity and BIO2040 Conservation biology
• GEN2041 Foundations of genetics and GEN2052 Genomics and population genetics

Business analytics

• ETC1000 Business and economic statistics
• ETC1010 Introduction to data analysis
• ETC2420 Statistical thinking
• ETC3550 Applied forecasting

Chemical sciences

• CHM1011 Chemistry 1 or CHM1051 Chemistry 1 Advanced
• CHM1022 Chemistry 2 or CHM1052 Chemistry 2 Advanced
• CHM2911 Inorganic and organic chemistry
• CHM2922 Spectroscopy and analytical chemistry

Crime and society

• ATS1421 Understanding crime
• ATS1423 Criminal justice in practice

Two of:

• ATS2456 Cybercrime and cybersecurity
• ATS2458 Policing
• ATS2465/ATS3465 Comparative criminal justice in practice (not offered in 2026)
• ATS2723 Social research methods

Cybersecurity

• FIT1047 Introduction to computer systems, networks and security
• FIT1093 Cybersecurity tools and techniques
• FIT2100 Operating systems
• FIT2173 Software security

Digital media

Two of:

• ATS1119 Communicating in the digital era
• ATS1206 Media challenges
• ATS1279 Media and culture

• ATS2250 Communications and Culture in the global era  (not offered in 2026)
• ATS2280 Video games: Industry and culture
• ATS2324 Climate change communication
• ATS2910 Professional and academic presentation skills

Discrete Mathematics

• BIO1011 Blueprints for life
• BIO1022 Life on earth 
• PHY2011 Neuroscience of communication, sensory and control systems
• PHA2022 Drugs and society

Economics

• ECC1000 Principles of microeconomics
• ECC1100 Principles of macroeconomics or ECX1200 Macroeconomics
• ECC2000 Intermediate Microeconomics or ECX2400 Design and evaluation of economic, public, and social programs 
• ECC2010 Intermediate Macroeconomics or ECX2300 Crashes, crisis and macroeconomic policy 

Introduction to physiology

• BIO1011 Blueprints for life or CHM1011 Chemistry 1 or CHM1051 Chemistry 1 Advanced or PHS1001 Foundation physics or PHS1011 Classical physics and relativity 
• BIO1022 Life on earth or CHM1022 Chemistry 2 or CHM1052 Chemistry 2 Advanced or PHS1022 Fields and quantum physics or PHS1002 Physics for engineering
• PHY2011 Neuroscience of communication, sensory and control systems
• PHY2032 Human physiology: Hormonal and digestive systems or PHY2042 Human physiology: Cardiovascular, respiratory and renal systems

Language and society

• ATS1338 Cracking the language code: English and beyond
• ATS1339 Linguistic structure and language diversity

Two of:

• ATS2274 Languages, cultures and interaction in Asia
• ATS2668 Structure in the languages of the world
• ATS2669 Phonetics and phonology: The science of speech sounds
• ATS2671 Managing intercultural communication
• ATS2769 Englishes around the world
• ATS3325 Embodied language: Gesture, gaze and interaction

Marketing science

• MKC1200 Principles of marketing
• MKC2130 Fundamentals of marketing analytics
• MKC2500 Marketing research analysis
• MKC3500 Advanced topics in marketing analytics

Physics 

• PHS1011 Classical physics and relativity or PHS1001 Foundation physics
• PHS1022 Fields and quantum physics or PHS1002 Physics for engineering

Two of:

• PHS2061 Quantum and thermal physics
• PHS2081 Atomic, nuclear and condensed matter physics

Social research

• ATS1365 Introduction to sociology
• ATS1366 Big ideas for better futures

Two of:

• ATS2560 Breaking binaries: How gender is lived and theorised
• ATS2561 Sex and the media
• ATS2716 Race, racism and social inequalities
• ATS2718 Love, families, and relationships
• ATS2720 Youth, culture and social change
• ATS2723 Social research methods
• ATS2727 Men, masculinity and society

Software development

• FIT1050 Web fundamentals

Three of:

• FIT2081 Mobile application development
• FIT2104 Web database interface
• FIT2175 Usability
• FIT3178 iOS app development

Part D. Advanced Practice (36 points)

You complete:

• ADS4001 Research methods
• ADS4010 Frontiers of data science
• ADS4100 Industry research project (24 points)

Part E. Free elective study (24 points)

You must complete 24 credit points of electives. Elective units in your Honours year must be at level 3 or higher, and be approved by the Honours Coordinator.

Elective units (12 credit points for stages 1-3 and 12 credit points for stage 4) may be chosen from the list of units from Parts B or C not already completed or from across the University as long as you have the prerequisites and there are no restrictions on admission to the units.

Free electives can be identified using the Advanced search tool in the current edition of the Handbook. The level of the unit is indicated by the first number in the unit code; undergraduate units are those that commence with the numbers 1-3. You may need permission from the owning faculty to enrol in some units taught by other faculties.