Bachelor of Data Science

The Bachelor of Data Science program is designed for high school graduates with or without programming experience who want to become data scientists.

It will prepare you for a career in data science, an emerging area driving economic growth, public policy and corporate strategy through management of very large collections of data to derive insights that ultimately benefit society.

Job titles for data scientists in this new field are very diverse, for example:

analytics specialist, business intelligence analyst, business intelligence developer, data analyst, data architect, data engineer, data miner, data scientist, research scientist and web analyst.In this program you will undertake a capstone project in the 12 credit point ONPS2186 Science Project 1 and 24 credit point course ONPS2669 Science Project.

These capstone project courses provide you with hands on practical experience analysing data in a project environment.

The emphasis is on understanding and working within a corporate environment and integrating all the skills and knowledge that you have acquired from your previous courses into a solid base to progress from into your professional life.This program is delivered on-campus requiring in person attendance.

Year One of Program

Complete the following Seven (7) Courses:

If you have not completed VCE Maths Methods or VCE Specialist Maths or equivalent, you must complete the following course:

Select and Complete One (1) Course from any:

AND

Year Two of Program

Complete the following Seven (7) Courses:

Select and Complete One (1) of the following Courses:

AND

Year Three of Program

Complete the following Five (5) Courses:

Select and Complete Two (2) Courses from any:

Program entry requirements

Successful completion of an Australian Year 12 senior secondary certificate of education or equivalent.

For information on international qualifications and corresponding entry requirements that are equivalent to Australian academic entry requirements, see the Country equivalents web page.

Prerequisites

Victorian Certificate of Education (VCE) Units 3 and 4: a study score of at least 30 in English (EAL) or at least 25 in English other than EAL; Units 3 and 4: a study score of at least 20 in any Mathematics.

English language requirements

A minimum IELTS (Academic module) overall score of 6.5, with no band below 6.0; or equivalent.

For equivalents to English entry requirements, see the English equivalents web page.

You are expected to develop the following Program Learning Outcomes:

Enabling Knowledge (PLO1)

You will gain skills as you apply knowledge with creativity and initiative to new situations. In doing so, you will:

• Demonstrate mastery of a body of knowledge that includes recent developments in computer science, information technology and statistics;
• Understand and use appropriate and relevant, fundamental and applied mathematical and statistical knowledge, methodologies and modern computational tools;
• Recognise and use research principles and methods applicable to data science.

Critical Analysis (PLO2)

You will learn to accurately and objectively examine, and critically investigate computer science, information technology (IT) and statistical concepts, evidence, theories or situations, in particular to:

• Analyse and manage large amounts of data arising from various sources
• Evaluate and compare solutions to data analysis problems on the basis of organisational and user requirements;
• Bring together and flexibly apply knowledge to characterise, analyse and solve a wide range of statistical problems.

Problem Solving (PLO3)

Your capability to analyse complex problems and synthesise suitable solutions will be extended as you learn to:

• Design and implement data analytic techniques that accommodate specified requirements and constraints, based on analysis or modelling or requirements specification;
• Apply an understanding of the balance between the complexity / accuracy of the mathematical / statistical models used and the timeliness of the delivery of the solution.

Communication (PLO4)

You will learn to communicate effectively with a variety of audiences through a range of modes and media, in particular to:

• Interpret abstract theoretical propositions, choose methodologies, justify conclusions and defend professional decisions to both technical and non-technical personnel via technical reports of professional standard and technical presentations.

Team Work (PLO5)

You will learn to work as an effective and productive team member in a range of professional and social situations, in particular to:

• Work effectively in different roles, to form, manage, and successfully produce outcomes from collaborative teams, whose members may have diverse cultural and educational backgrounds and life circumstances, and differing levels of technical expertise.

Responsibility (PLO6)

You will be required to accept responsibility for your own learning and make informed decisions about judging and adopting appropriate behaviour in professional and social situations. This includes accepting the responsibility for independent life-long learning and a high level of accountability. Specifically, you will learn to:

• Effectively apply relevant standards, ethical considerations, and an understanding of legal and privacy issues to managing and processing data;
• Contextualise outputs where data are drawn from diverse and evolving social, political and cultural dimensions;
• Reflect on experience and improve your own future practice;
• Locate and use data and information and evaluate its quality with respect to its authority and relevance.