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:

• FIT1045 Algorithms and programming fundamentals in python
• FIT1008 Introduction to computer science
• MAT1830 Discrete mathematics for computer science
• FIT2086 Modelling for data analysis
• FIT3154 Advanced data analysis
• FIT3181 Deep learning

and

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

• MTH1020 Analysis of change^
• MTH1030 Techniques for modelling or MTH1035 Techniques for modelling (advanced)
• MTH2019 Multivariate mathematics for data science
• MTH2222 Maths of uncertainty or MTH2051 Introduction to computational mathematics
• MTH3241 Random processes in the sciences and engineering or MTH3320 Computational linear algebra
• MTH3330 Optimisation and operations research

* If you completed VCE Specialist mathematics and achieved a raw score of 30 or higher replace the first three units in the sequence with the following:

• MTH1030 Techniques for modelling or MTH1035 Techniques for modelling (advanced)
• MTH2010 Multivariable calculus or MTH2015 Multivariable calculus (advanced)
• MTH2021 Linear algebra with applications or MTH2025 Linear algebra (advanced)

Note 1: Students admitted into the course from Gaokao must complete MTH1010 Functions and their applications prior to MTH1020 Analysis of change. MTH1010 will count as an elective.

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)

Anatomy and developmental biology

• BIO1011 Blueprints for life
• BIO1022 Life on earth or BIO1042 Life in the environment
• DEV2011 Early human development from cells to tissues
• DEV2022 Human anatomy and development: Tissues and body systems

Applied and statistical mathematics

• MTH2132 The nature and beauty of mathematics
• STA1010 Statistical methods for science

two of:

• MTH2222  Mathematics of uncertainty
• MTH2232 Mathematical statistics
• MTH2032 Differential equations 
• MTH2051 Introduction to computational mathematics

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 Foundations physics
• PHS1002 Physics for engineering

And

• ASP2011 Astronomy
• ASP2062 Introduction to astrophysics

Biochemical science

• BIO1011 Blueprints for life or CHM1011 Chemistry 1 or CHM1051 Chemistry 1 Advanced
• BIO1022 Life on earth or CHM1022 Chemistry 2 or CHM1052 Chemistry 2 Advanced
• BCH2011 Structure and functions of cellular biomolecules 
• BCH2022 Metabolic basis of human diseases