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Applied Data Science

Interested in mastering big data and helping others to understand it? This is the course for you.

Course Introduction

We are excited to be bringing the new Bachelor of Applied Data Science, and the Bachelor of Applied Data Science Advanced (Honours) to Monash University. Research and analysis with big datasets is making a positive impact on our daily lives across a very wide range of disciplines.

Our new Applied Data Science programs, available from 2020, will deal with the challenges that large bodies of data present to research, industries, and society.

These courses represent a key component of broader cross-faculty data science initiatives at Monash.

Data Science is one of the hottest topics in technology and is a highly in-demand field, but there is a shortage of skilled, qualified data scientists worldwide.

Our world-class staff and teaching environment will provide you with a globally recognised education and the skills to make a difference in the world of Data Science.

Career outcomes

“In this data-dominated era, everything  and everyone produces a digital paper  trail. If businesses want to gain an edge, they need to be able to tap into those large, elusive data sets to make better decisions about how products are built, markets are found, clients and employees are supported, and sales are generated. Hence the need  for data scientists.”
– Forbes

Upon successful completion of the degree, possible careers for graduates could include:

  • Business intelligence analyst
  • Data architect
  • Data mining engineer
  • Data scientist
  • Quantitative analyst

In a range of industries, including: Digital humanities, Energy, Natural resources and utilities, Cybersecurity, Urban planning and transport, Biotechnology and pharmaceuticals, Marketing, Engineering and robotics, Sport, Banking, Finance and insurance.

COURSE STRUCTURE


1. Bachelor of Applied Data Science

If you’re interested in mastering big data and helping others to understand it, this is the course for you. This program of study will provide you with the skills necessary to solve a wide range of problems. This is a specialist course which will develop your technical know-how in being able to approach data challenges.

Through selected streams, you’ll develop your passion for the physical sciences, sociological or anthropological studies, business or engineering. Working in groups and on individual projects, you’ll bring together key skills in IT and mathematics, and apply these to real-life projects.

YEAR 1

Semester 1

ADS1001

Data challenges 1

MAT1830

Discrete mathematics for computer science

MTH1020 Analysis of change or MTH1030 Techniques for modelling or MTH1035 Techniques for modelling (advanced)

Applied studies*


YEAR 1

Semester
2

ADS1002

Data challenges 2

FIT1045

Algorithms and programming fundamentals in python

MTH1030 Techniques for modelling or MTH1035 Techniques for modelling (advanced) or MTH2010 Multivariable calculus or MTH2015 Multivariable calculus (advanced)

Applied studies*


YEAR 2

Semester 1

ADS2001

Data challenges 3

FIT1008

Introduction to computer science

MTH2019 Multivariate mathematics for data science or MTH2021 Linear algebra with equations or MTH2025 Linear algebra (advanced)

Applied studies*


YEAR 2

Semester 2

ADS2002

Data challenges 4

FIT2086

Modelling for data analysis

MTH2222 Mathematics of uncertainty or MTH2051 Introduction to computational mathematics

Applied studies*


YEAR 3

Semester 1

FIT3154

Advanced data analysis

FIT3181

Applied deep learning

MTH3241 Random processes in the sciences and engineering or MTH3320 Computational linear algebra

Free elective


YEAR 3

Semester 2

ADS3001

Advanced data challenges (12 points)

MTH3330

Optimisation and operations research

Free elective


Legend

Part A: Data challenges
Part B: Techniques for data science
Part C: Applied studies*
Part D: Free elective

*Anatomy and developmental biology, Applied and statistical mathematics, Astronomy, Biochemical science, Biological science and genetics, Business analytics, Business information systems, Chemical sciences, Computer systems engineering, Crime and society, Cybersecurity, Digital humanities, Discrete mathematics, Drugs and society: an introduction to pharmacology, Earth and atmospheric sciences, Geography and the environment, Interactive media, Introduction to the microbial world, Introduction to molecular and cell biology, Introduction to physiology, Language and society, Marketing science, Mobile applications development, Physics, Social research and Software development.

Prerequisites

VCE

English: Units 3 and 4: a study score of at least 30 in English (EAL) or 25 in English other than EAL.
Maths: Units 3 and 4: a study score of at least 25 in Mathematical Methods (any) or Specialist Mathematics.

IB

English: Level 1.
Maths: Level 3.

Our VTAC Subject Adjustment Bonus

This rewards students studying more than one of the following Year 12 science subjects;
Algorithms (HESS), Biology, Chemistry, Environmental Science or Physics – this could improve your ranking and eligibility by providing additional points towards your ATAR aggregate.

2. Bachelor of Applied Data Science Advanced (Honours)

This is an advanced degree program for those passionate about Data Science.

This four-year specialist course brings together studies in IT and mathematics in a series of interdisciplinary problem-solving challenges.

Research and analysis into big data have the capacity to make a positive impact on our daily lives. This degree will give you the skills necessary to provide solutions to a wide range of problems.

Through selected streams, you’ll develop your passion for the physical sciences, sociological or anthropological studies, business or engineering. Working in groups and on individual projects, you’ll bring together key skills in IT and mathematics, and apply these to real-life projects.

YEAR 1

Semester 1

ADS1001

Data challenges 1

MAT1830

Discrete mathematics for computer science

MTH1020 Analysis of change or MTH1030 Techniques for modelling or MTH1035 Techniques for modelling (advanced)

Applied studies*


YEAR 1

Semester 2

ADS1002

Data challenges 2

FIT1045

Algorithms and programming fundamentals in python

MTH1030 Techniques for modelling or MTH2040 modelling

Applied studies*


YEAR 2

Semester 1

ADS2001

Data challenges 3

FIT1008

Introduction to computer science

MTH2021 Linear algebra with equations or MTH2222 Mathematics of uncertainty

Applied studies*


YEAR 2

Semester 2

ADS2002

Data challenges 4

FIT2086

Modelling for data analysis

MTH2051

Introduction to computational mathematics

Applied studies*


YEAR 3

Semester 1

FIT3154

Advanced data analysis

FIT3181

Applied deep learning

MTH3241 Random processes in the sciences and engineering or MTH3320 Computational linear algebra

Free elective


YEAR 3

Semester 2

ADS3001

Advanced data challenges (12 points)

MTH3330

Optimisation and operations research

Free elective


YEAR 4

Semester 1

ADS4001

Research methods

ADS4010

Frontiers of data science

Free elective

Free elective


YEAR 4

Semester 2

ADS4100

Industry research project (24 points)


Legend

Part A: Data challenges
Part B: Techniques for data science
Part C: Applied studies*
Part D: Advanced practice
Part E: Free elective

*Anatomy and developmental biology, Applied and statistical mathematics, Astronomy, Biochemical science, Biological science and genetics, Business analytics, Business information systems, Chemical sciences, Computer systems engineering, Crime and society, Cybersecurity, Digital humanities, Discrete mathematics, Drugs and society: an introduction to pharmacology, Earth and atmospheric sciences, Geography and the environment, Interactive media, Introduction to the microbial world, Introduction to molecular and cell biology, Introduction to physiology, Language and society, Marketing science, Mobile applications development, Physics, Social research and Software development.

Prerequisites

VCE

English: Units 3 and 4: a study score of at least 30 in English (EAL) or 25 in English other than EAL.
Maths: Units 3 and 4: a study score of at least 30 in Mathematical Methods or Specialist Mathematics.

IB

English: Level 1.
Maths: Level 3+.

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E: future@monash.edu
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