Admission to our undergraduate degree programs usually requires successful completion of a senior secondary school qualification similar to the Higher School Certificate (HSC), the highest educational award in New South Wales schools.
Program handbook
Description
The computing, mathematics and technology industries are at the forefront of new thinking, and are central to the way we work, learn, communicate, socialise and entertain ourselves. Through this program, you might mathematically model the way diseases spread to find a cure for malaria or search for algorithms to speed up computations. By studying the Bachelor of Data Science/Bachelor of Mathematics, you will develop core skills and content in data science and mathematics including data wrangling and visualisation, optimisation, mathematical modelling, complex analysis, predictive analytics, programming, data security, and applied artificial intelligence including machine intelligence.
Program learning outcomes
On successful completion of the program students will have:
- Expertise: You will be a data scientist who can draw on a body of knowledge that spans data science, data analytics, data architecture, data engineering, and data wrangling, to apply yourself across a range of professions, projects, and problems.
- Awareness: You will be to apply your learning and skills to create new understandings of the world and real world issues that lay at the intersection of many traditional and emerging disciplines.
- Tenacity: You will be a problem solver and an innovator who can identify, draw upon and manage resources to take a project from concept to completion.
- Perception: You will be a critical thinker who has keen insight and a broad perspective of the world to find solutions to complex problems.
- Responsiveness: You will be a person who has the flexibility to work in many different environments, to harness collective knowledge within local and global professional networks, to communicate effectively, to work with people and have an appreciation of others.
- Integrity: You will be a professional who can apply your skills and knowledge of data science to the highest ethical standards responsibly and honestly.
- Knowledge: You will possess in-depth knowledge and skills in at least one area of mathematics to a depth sufficient for further study, research or employment as a mathematician or statistician or data scientist; with proficiency in the fundamentals of mathematics or statistics; and an awareness of areas of mathematics/statistics and understanding of connections between them.
- Understanding: You will have the ability to formulate mathematical/statistical problems, validate mathematical/statistical models and to interpret their results, and apply and adapt mathematical or statistical knowledge to a wide range of situations.
- Skills: You will be a problem-solver who will use their judgement and ability to form conjectures and test them using mathematical or statistical methods, reason formally from hypotheses to conclusions, develop mathematical/ statistical methods to solve problems, and will be experienced in the use of mathematical and statistical resources from the literature or in computational tools.
- Responsiveness: You will be able to effectively communicate with the mathematical and broader community, using mathematical or statistical tools to assimilate and articulate mathematical/statistical concepts and arguments with clear and systematic reasoning in an appropriate form.
- Flexibility: You will be able to work in many different environments and have the capacity to both work independently as well collaboratively as part of a team.
- Ethical Practice: You will have an understanding of the importance of standards of mathematical practice within the profession and broader community, an awareness of the importance of using appropriate mathematical and statistical models, the ability to validate the reliability of mathematical and/or statistical techniques and cognisant of their scope, and a commitment to keep up with developments in mathematics/statistics.
Details
Information correct as at | 25 Feb 2021 4:23 pm | |||
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Program code | 40277 | |||
Locations and UAC codes | ||||
Mode of delivery |
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Duration |
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Selection Rank |
This program is new for 2021, there is currently no commencing student profile available. | |||
Assumed knowledge | HSC Mathematics Advanced or equivalent | |||
Recommended studies | HSC Mathematics Extension 1 or equivalent | |||
Term type | Semesters | |||
Fees | ||||
Relevant University rules and policies |
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Admission information
Admission requirements
Admission to this program is available to Australian students, residents and international students. Admission information for Australian students and residents is available online here. Admission information for international students can be found here. During the admission process adjustment factors may be applied to your Selection Rank. Please visit our website to see if you are eligible.
Minimum English language proficiency requirements
All Applicants must demonstrate that they meet the University’s English proficiency requirement. Further information regarding English language proficiency requirements can be found at the English Language Proficiency for Admission Policy here.
Credit transfer
If you wish to apply for credit for studies completed at another institution, or if you are changing programs within the University and wish to transfer your credit to the new program, visit the University's credit website for more information on applying for credit.
Academic requirements for program completion
Total units required
320 units
Program duration
4 years full-time or part-time equivalent up to 10 years maximum.
Program requirements
The Bachelor of Data Science/Bachelor of Mathematics requires students to pass courses totalling 320 units, as follows:
- 210 units of Core courses
- 110 units from either the Pure and Applied Mathematics Major or the Statistics Major as follows
The Pure and Applied Mathematics Major is comprised of the following 110 units:
- 20 units of Compulsory courses
- 40 units of Group A Directed courses
- 10 units of Group B Directed courses
- 40 units of Electives
The Statistics Major is comprised of the following 110 units:
- 50 units of Compulsory courses
- 60 units of Electives
Please note: Students must only complete courses that form part of the program. Electives include any unrestricted courses offered within the university.
Some core courses count towards each major:-
Pure and Applied Mathematics Major: MATH1120, MATH1800
Statistics Major: STAT1100, STAT1300, STAT2300
Program structure
Students are advised to read their program handbook information in conjunction with the program plans for course sequence/enrolment advice. Please refer to the Program Plan for the year that you commenced, or transitioned into, this program - Program Plans are available above.
Advanced course filters
Courses that are currently unavailable are hidden by default. You can show them by adjusting the advanced course filters above, or clicking the 'show all' links below each section.
Core Courses
Complete the following core courses. | |||
Code | Title | Term / Location | Units |
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COMP1140 | Database and Information Management |
| 10 units |
MATH1110 | Mathematics for Engineering, Science and Technology 1 |
| 10 units |
MATH1120 | Mathematics for Engineering, Science and Technology 2 |
| 10 units |
MATH1510 | Discrete Mathematics |
| 10 units |
MATH1800 | Mathematical Modelling |
| 10 units |
SENG1110 | Object Oriented Programming |
| 10 units |
SENG1120 | Data Structures |
| 10 units |
STAT1100 | Data Wrangling and Visualisation |
| 10 units |
STAT1300 | Fundamentals of Statistics |
| 10 units |
COMP2230 | Algorithms |
| 10 units |
INFT2150 | Business Analysis |
| 10 units |
MATH2310 | Calculus of Science and Engineering |
| 10 units |
MATH2340 | Linearity and Continuity 1 |
| 10 units |
MATH2350 | Linearity and Continuity 2 |
| 10 units |
STAT2020 | Predictive Analytics |
| 10 units |
STAT2300 | Statistical Inference |
| 10 units |
COMP3260 | Data Security |
| 10 units |
COMP3330 | Machine Intelligence |
| 10 units |
COMP3340 | Data Mining |
| 10 units |
COMP3851A | Computer Science and Information Technology Work Integrated Learning Part A |
| 10 units |
COMP3851B | Computer Science and Information Technology Work Integrated Learning Part B |
| 10 units |
Pure and Applied Mathematics Major
Compulsory Courses | |||
Complete the following compulsory courses. | |||
Code | Title | Term / Location | Units |
---|---|---|---|
MATH2242 | Complex Analysis |
| 10 units |
MATH2800 | Ordinary Differential Equations |
| 10 units |
Group A Directed Courses | |||
Complete 40 units from the following directed courses. | |||
Code | Title | Term / Location | Units |
---|---|---|---|
MATH3120 | Algebra |
| 10 units |
MATH3170 | Number Theory |
| 10 units |
MATH3205 | Fourier Analysis |
| 10 units |
MATH3700 | Partial Differential Equations |
| 10 units |
MATH3820 | Numerical Methods |
| 10 units |
Group B Directed Courses | |||
Complete 10 units from the following directed courses. | |||
Code | Title | Term / Location | Units |
---|---|---|---|
INFT3800 | Professional Practice in IT |
| 10 units |
STAT3030 | Generalised Linear Models |
| 10 units |
STAT3040 | Forecasting with Linear Time Series Models |
| 10 units |
Statistics Major
Compulsory Courses | |||
Complete the following compulsory courses. | |||
Code | Title | Term / Location | Units |
---|---|---|---|
STAT2000 | Applied Statistics and Research Methods |
| 10 units |
STAT3030 | Generalised Linear Models |
| 10 units |
STAT3040 | Forecasting with Linear Time Series Models |
| 10 units |
STAT3100 | Systems Thinking for an Integrated Workforce |
| 10 units |
STAT3800 | Deterministic and Stochastic Optimisation |
| 10 units |
Additional information
All students can access free academic skills and support provided by Academic Learning Support through the Pathways and Academic Learning Support Centre.
Aboriginal and Torres Strait Islander students can draw on the assistance and support provided by the Indigenous Student Support and Development service through the Wollotuka Institute.
International students
All International Students enrolled in the program will be provided with an orientation to familiarise them with the rules, expectations, facilities and services offered by the University. Please visit our International Students website to find out more about the support services available to international students.
Additional support
AccessAbility provides advice and reasonable adjustments to Students with a medical or health condition or disability. If you require adjustments to undertake your program, contact the Student Support Advisors - AccessAbility before semester or early in the semester. They will work with the Faculty or School to ensure that this happens in a timely manner.
Please note: All students must fulfil the inherent requirements of the programs and courses they are undertaking. While reasonable adjustments can be made, these adjustments cannot compromise academic integrity. It is the student's responsibility to check all the requirements of courses, and consider the effects of any medical condition or disability on their ability to complete course requirements. More information is available online.