Bachelor of Data Science (Honours)

Course summary for international students

Year	2026 course information
Award granted	Bachelor of Data Science (Honours)
Campus	Offered at Burwood (Melbourne), Online
Length	4 years full-time
Fee paying annual fee - commencing 2026	$42,000 for 1 yr full-time AUD
Level	Undergraduate
CRICOS code	109275A Burwood (Melbourne)
VTAC codes	1400511373 - Burwood (Melbourne), International full-fee paying place
Deakin course code	S479
Australian Qualifications Framework (AQF) recognition	The award conferred upon completion is recognised in the Australian Qualifications Framework at Level 8

Course sub-headings

Course overview

Explore the entire lifecycle of data and develop a deep understanding of how information is transformed into insights that drive strategic business decisions. During the Bachelor of Data Science (Honours), you will have the opportunity to complete a professional placement or work in teams with an industry partner to solve authentic business challenges using real-world data sets. Hone your skills through focused studies in your area of interest and complete a research project in your final year.

Propel yourself into the thriving field of data science. You will study the latest data science trends, insights and emerging topics to ensure you graduate with a highly relevant skill set that is sought after by employers across the globe. Explore different analytical methods, tools and techniques as you learn key concepts and deep dive into advanced topics in machine learning, AI and predictive analytics.

Want to hone your analytical skills for a rewarding career in data science?

The Bachelor of Data Science (Honours) gives you ample opportunity to sharpen your skill set under the guidance and direction of our supportive teaching staff. You’ll explore fundamental concepts across maths, stats and programming at the beginning of the course, before diving into more advanced topics in data management; data modelling and design; data wrangling, capture and mining; software development; machine learning; deep learning and AI. You can focus your studies towards your area of interest by undertaking minor studies in a topic of your choosing. In your final year, consolidate your knowledge through the completion of an honours research project.

Professional recognition

The Bachelor of Data Science (Honours) is professionally accredited with the Australian Computer Society (ACS). This course is recognised internationally for entry to professional practice by other accrediting bodies through the Seoul Accord.

Fees and charges

The tuition fees you pay are determined by the course you are enrolled in. The 'Estimated tuition fee' is provided as a guide only and represents the typical first-year tuition fees for students enrolled in this course. The cost will vary depending on the units you choose, your study load, the length of your course and any approved Recognition of prior learning you have.

Each unit you enrol in has a credit point value. The 'Estimated tuition fee' is calculated by adding together eight credit points of a typical combination of units for this course. Eight credit points is used as it represents a typical full-time enrolment load for a year.

You can find the credit point value of each unit under the Unit Description by searching for the unit in the handbook.

Learn more about international student fees.

Career opportunities

According to the World Economic Forum’s ‘Future of Jobs Report 2025’, big data specialists top the list of the fastest-growing roles globally. Data warehousing specialists, along with data analysts and scientists, also rank within the top 12. This course provides you with the cutting-edge knowledge and hands-on experience to stand out in this booming industry.

As a graduate, you will have the skills, knowledge and industry connections to build a varied and sustainable career as a data analyst, data scientist, business strategist, data engineer, data architect, data visualisation specialist, information analyst or reporting analyst in the public and private sectors. Depending on your chosen industry or sector, you could be optimising digital marketing campaigns, developing new and innovative products and services, predicting customer sales patterns, or increasing productivity in areas such as sales or supply chain management.

Graduates from the Bachelor of Data Science (Honours) are highly sought after by employers for their investigative, exploratory and lateral-thinking approach to complex data challenges. By undertaking a focused research project in your final year of study, you will acquire advanced technical expertise in your chosen specialisation. Plus, you will have the skills to become a creative, solutions-driven professional in the dynamic and ever-evolving field of data science.

Course learning outcomes

Deakin Graduate Learning Outcomes	Course Learning Outcomes
Discipline-specific knowledge and capabilities	Develop a coherent and advanced knowledge of data science, with detailed knowledge of the data analytics principles and approaches and knowledge, skills, tools, and methodologies for professional practice and research.
Communication	Communicate in a professional context incorporating research-driven perspective to inform, explain and drive sustainable innovation through data science, utilising a range of verbal, graphical and written methods, recognising the needs of diverse audiences.
Digital literacy	Identify, select and use digital technologies, platforms, frameworks, and tools from the field of data science to generate, manage, process and share digital resources for research and practice.
Critical thinking	Critically analyse information provided to inform decision making and evaluation of plans and solutions associated with research and practice in data science.
Problem solving	Apply cognitive, technical, and creative skills from data science to understand requirements and design, implement, operate, and evaluate innovative solutions to real-world and ill-defined computing problems.
Self-management	Work independently to apply knowledge and skills to new situations in research and professional practice and/or further learning in the field of data science with adaptability, autonomy, responsibility, and personal accountability for actions as a practitioner and a learner.
Teamwork	Work independently and collaboratively to achieve team goals, contributing knowledge and skills from data science practice and research to advance the teams objectives, employing effective teamwork practices and principles, and comprehending distinct workplace roles and their functions.
Global citizenship	Apply professional and ethical standards and accountability in research and practice in the field of data science, and engage openly and respectfully with diverse communities and cultures.

Course rules

To complete the Bachelor of Data Science (Honours), you must pass 32 credit points. This includes:

DAI001 Academic Integrity and Respect at Deakin (0-credit-point compulsory unit) in your first study period
STP010 Career Tools for Employability (0-credit-point compulsory unit)
17 credit points of core units
3 credit points of data science capstone units
4 credit points of data science research training capstone units
8 credit points which may comprise of:
- 2 minors (8 credit points)
- 1 minor (4 credit points) and 4 credit points of open elective units
a maximum of 10 credit points at level 1
a minimum of 10 credit points at level 3 or above.

Most units are equal to one credit point. As a full-time student you will study four credit points per trimester and usually undertake two trimesters per year.

All students are required to meet the University's academic progress and conduct requirements.

Minors

Refer to the details of each minor sequence for availability.

Students wishing to complete two minor sequences in the Bachelor of Data Science (Honours) cannot count more than 2 units in common for both minor sequences.

Course structure

Core units

Year 1 - Trimester 1

DAI001

Academic Integrity and Respect at Deakin (0 credit points)

STP010

Career Tools for Employability (0 credit points)

SIT111

Computer Systems

SIT192

Discrete Mathematics

SIT112

Introduction to Data Science and Artificial Intelligence

SIT102

Introduction to Programming

Year 1 - Trimester 2

SIT103

Database Fundamentals

SIT191

Introduction to Statistics and Data Analysis

SIT232

Object-Oriented Development

SIT292

Linear Algebra for Data Analysis

Year 2 - Trimester 1

SIT202

Computer Networks and Communication

SIT220

Data Wrangling

SIT221

Data Structures and Algorithms

Plus 1 minor or open elective unit (1 credit point)

Year 2 - Trimester 2

SIT223

Professional Practice in Information Technology #

SIT343

Feature Generation and Engineering

SIT225

Data Capture Technologies

Plus 1 minor or open elective unit (1 credit point)

Year 3 - Trimester 1

SIT330

Natural Language Processing

SIT307

Machine Learning

SIT374

Team Project (A) - Project Management and Practices ^ (capstone)

Plus 1 minor or open elective unit (1 credit point)

Year 3 - Trimester 2

SIT319

Deep Learning

Plus 1 minor or open elective unit (1 credit point)

Plus 2 credit points from the following capstone options:

SIT378

Team Project (B) - Execution and Delivery ^ (capstone)

SIT306

IT Placements and Industry Experience ^+ (capstone)

SIT344

Professional Practice (2 credit points)^+ (capstone)

Year 4 - Trimester 1

SIT723

Research Techniques and Applications (2 credit points) (research training capstone)^

Plus 2 open electives or minor units (2 credit points)

Year 4 - Trimester 2

2 open electives or minor units (2 credit points)

Plus two (2) credit points from the following research training capstone options:

SIT724

Research Project (2 credit points)^ (research training capstone)

SIT746

Research Project (Advanced) (2 credit points)^* (research training capstone)

^ Offered in Trimester 1, Trimester 2 and Trimester 3

# Corequisite of STP010 Career Tools for Employability (0-credit point compulsory unit)

+ Students must have completed STP010 Career Tools for Employability (0-credit point compulsory unit) and SIT223 Professional Practice in Information Technology.

* Entry to SIT746 is subject to specific unit entry requirements.

It is important to ensure your course plan meets the course rules detailed above. Students should contact Student Central for assistance with course planning, choosing the right units and understanding course rules.

Electives

Select from a range of elective units offered across many courses. In some cases you may even be able to choose elective units from a completely different discipline area (subject to meeting unit requirements).

Equipment requirements

The learning experiences and assessment activities within this course require that students have access to a range of technologies beyond a desktop computer or laptop. Students will be required to purchase minor equipment, such as small single board computers, microcontrollers and sensors, which will be used within a range of units in this course. This equipment is also usable by the student beyond their studies. Equipment requirements and details of suppliers will be provided on a per-unit basis. The indicative cost of this equipment for this course is AUD$500.

For information regarding hardware and software requirements, please refer to the Bring your own device (BYOD) guidelines via the School of Information Technology website in addition to the individual unit outlines in the Handbook.

Admission criteria

Selection is based on a holistic consideration of your academic merit, work experience, likelihood of success, availability of places, participation requirements, regulatory requirements, and individual circumstances. You will need to meet the minimum academic and English language proficiency requirements to be considered for selection, but this does not guarantee admission.

A combination of qualifications and experience may be deemed equivalent to minimum academic requirements.

If you don't meet the academic entry requirements as outlined in the tabs below, or haven't completed Year 12, or don't hold any relevant qualifications, the STAT (Skills for Tertiary Admissions Test) Multiple Choice (MC) may be an option for you to meet course entry requirements.

Academic requirements

Academic requirements - Higher education study

If you’re currently studying Year 12, or completed Year 12 in the last two years, you will need to meet all the following criteria to be considered for admission to this degree:

Year 12 prerequisite subjects

Units 3 and 4: a study score of at least 25 in English EAL (English as an Additional Language) or at least 20 in English other than EAL

ATAR

Senior Secondary Certificate of Education with an unadjusted ATAR of at least 50 or equivalent

Academic requirements - Higher education study

If you have undertaken higher education studies after secondary schooling, you will need to meet all the following criteria to be considered for admission to this degree:

successful completion of at least two bachelor level or above units (AQF Level 7 or equivalent) with a minimum WAM of 70 or equivalent

Academic requirements - VET study

If you have undertaken any Vocational Education and Training (VET) study after secondary school, you will need to meet at least one of following criteria to be considered for admission to this degree:

completion of a certificate IV or higher in a related discipline
completion of a diploma or higher in any discipline
at least 50% completion of a diploma or higher in a related discipline

Academic requirements - Work and life experience

If you finished Year 12 more than three years ago, or did not finish Year 12, and haven't undertaken any further study, you may be considered for admission to this degree based on your work, volunteer and/or life experience.

Submit a personal statement outlining your motivation to study, previous education and employment history, and how this course can assist your career aspirations or progression. Think of it as a job application cover letter - it should be relevant and demonstrate your commitment and interest in this course or study area.

English language proficiency requirements

To meet the English language proficiency requirements of this course, you will need to demonstrate at least one of the following:

Victorian Certificate of Education (VCE) English Units 3 and 4: Study score of 25 in English as an Additional Language (EAL) or 20 in any other English
IELTS overall score of 6.0 (with no band score less than 6.0) or equivalent
other evidence of English language proficiency (learn more about other ways to satisfy the requirements)

Admissions information

Learn more about Deakin courses and how we compare to other universities when it comes to the quality of our teaching and learning. We're also committed to admissions transparency. Read about our first intake of 2026 students (PDF, 879KB) – their average ATARs, whether they had any previous higher education experience and more.

Not sure if you can get into Deakin? Discover the different entry pathways we offer and study options available to you, no matter your ATAR or education history.

Credit for prior learning - general

If you have completed previous studies which you believe may reduce the number of units you have to complete at Deakin, indicate in the appropriate section on your application that you wish to be considered for Recognition of prior learning. You will need to provide a certified copy of your previous course details so your credit can be determined. If you are eligible, your offer letter will then contain information about your Recognition of prior learning.
Your Recognition of prior learning is formally approved prior to your enrolment at Deakin during the Enrolment and Orientation Program. You must bring original documents relating to your previous study so that this approval can occur.

You can also refer to the recognition of prior learning (RPL) system which outlines the credit that may be granted towards a Deakin University degree.

Alternative exits

Bachelor of Data Science (S379)

Further study

The Bachelor of Data Science (Honours) may be used as further study pathways into a postgraduate preservice teaching qualification through the Master of Applied Learning and Teaching and the Master of Teaching, which has options for Primary and Secondary teaching.

A Bachelor of Data Science (Honours) may also provide you with the opportunity to pursue a research pathway to Higher Degree by Research.

Course duration

You may be able to study available units in the optional third trimester to fast-track your degree, however your course duration may be extended if there are delays in meeting course requirements, such as completing a placement.

Workload

You can expect to participate in a range of teaching activities each week. This could include classes, seminars, practicals and online interaction. You can refer to the individual unit details in the course structure for more information. You will also need to study and complete assessment tasks in your own time.

Work experience

This course includes a compulsory work placement with an approved host organisation to take your learning beyond the classroom and prepare you to be work and career ready. Work Integrated Learning (WIL) units offered in this course provide you with the opportunity to develop your professional networks and work practices while completing your degree.

Elective units may also provide additional opportunities for work integrated learning experiences.

For more information visit SEBE Work Integrated Learning.

Participation requirements

Placement can occur at any time, including during standard holiday breaks. Learn about key dates at Deakin.

Elective units may be selected that include compulsory placements, work-based training, community-based learning or collaborative research training arrangements.

Reasonable adjustments to participation and other course requirements will be made for students with a disability. More information available at Disability support services.

Mandatory student checks

Any unit which contains work integrated learning, a community placement or interaction with the community may require a police check, Working with Children Check or other check.

Selection adjustment

Access and equity

Equity schemes and scholarships, formerly known as Special Entry Access Schemes (SEAS), enable Deakin to consider any disadvantaged circumstances you may have experienced and how these have impacted your studies. Equity schemes help us identify whether you are from an under-represented group when making selection decisions for certain courses. It's important to note that participation in an equity scheme does not exempt you from meeting the standard course entry requirements. Learn more about Deakin's equity schemes and scholarships.