S3003 - Bachelor of Applied Data Science Advanced (Honours)

Overview

We live in a time where information and knowledge have never been more abundant. From industry leaders and NGOs to policy makers, from educators to research specialists, the decisions that shape our future will rely on graduates who can extract meaning from large volumes of data and transmit it to community and industry leaders.

The Bachelor of Applied Data Science Advanced (Honours) is an advanced program of study that will equip you with the skills necessary to provide solutions to a wide range of problems. Working in groups and on individual projects, you will bring together key skills in information technology and mathematics and apply these to real life projects. Through selected streams, you will develop your passion for the physical sciences, sociological or anthropological studies, biomedical studies, business or engineering. The unique blend of skills that you will attain upon completion of the program will empower you to apply data science to a wide range of industries and make them highly desirable problem solvers.

Notes

You can enrich your degree to hone your academic and professional skills with a range of flagship rich educational experiences. These flagship rich educational experience units may be credited in place of your discipline specific electives (up to 6 credit points) if approved by the faculty, or alternatively utilising your free electives. There are both 6 and 12 credit point unit options available.*

*If you are enrolled in a double degree there may be space available in the non-science side of your double degree to undertake flagship rich educational experiences. For information on eligible double degree combinations please see Flagship Rich Educational Experiences.

Mode and location

On campus

Learning outcomes

These course outcomes are aligned with the Australian Qualifications Framework and Monash Graduate Attributes.

Upon successful completion of this course it is expected that you will be able to:

demonstrate advanced knowledge and technical skills in data science

design, implement and apply methods for capturing, managing and analysing data

listen, understand, and communicate persuasively to a variety of audiences using a variety of formats

apply critical thinking and problem solving strategies to develop efficient solutions to a range of authentic challenges

develop leadership and enterprising skills to create and implement effective solutions

develop multicultural literacy and knowledge and apply these across a variety of industries that may include government, academic, private and social-good enterprises

demonstrate an understanding of the importance of leadership, social responsibility, ethics and mentoring

apply research methodologies to conduct significant independent research.

Structure

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.

Requirements
192 credit points

Rules

The course comprises 192 credit points of which 168 credit points are focussed on Applied Data Science. No more than 10 units (60 credit points) are to be completed at Level 1 in the course.

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

Part A. Data challenges36 credit points

Part B. Techniques for data science72 credit points

Information technology units 36 credit points

You must complete the following units.
Note: You can only complete one of FIT3152 or FIT3154.

Overview

Notes

Mode and location

Learning outcomes

Structure

Requirements192 credit points

Alternative exit(s)

Progression to further studies

Organisational contact information

Requirements
192 credit points