Program handbook

Description

Advances in the scientific and technological sectors have caused an enormous explosion in the volume of data generated. As the volume and complexity of data increases, a workforce with skills and qualifications in data management and analysis will be in greater demand. In recent years, data scientist/analyst and related careers have been consistently ranked among the top jobs and most in-demand skills requested by employers.

The University of Newcastle's Master of Data Science will equip students with the essential professional skills and knowledge to understand and engage with a variety of data generated from diverse industries and settings. Graduates will learn how to manage, analyse, interpret, visualise and effectively communicate data. They will also learn how to use data to model real-word situations.

The program is professional in nature and industry oriented. Students will learn to understand and explore data using applied problem solving and computer practice. All learning will be underpinned by the required theoretical knowledge.The core courses cover foundational areas, such as data wrangling and visualisation, databases, predictive analytics, big data, and statistics.

Students will complete a specialisation in either Computational Intelligence or Health Data Analysis. The Computational Intelligence specialisation is aligned to a computer science approach to data science, which includes further studies in data mining and machine learning. The Health Data Analysis specialisation focuses on medical statistics, biostatistics, and related areas, while providing transferrable data analysis skills also applicable to other domains.

Please note that students who commence in Semester 1 can complete the program in a minimum of 2 years full time. Students who commence in Semester 2 can complete the program in a minimum of 1.5 years full time.

 


Program learning outcomes

On successful completion of the program students will have:

  • Specialised knowledge of statistical and computational models and concepts and proficiency in their application.
  • Specialist knowledge in statistical and computational techniques for analysing and interpreting data sets.
  • Critical thinking and analytical problem solving to support data management and data-oriented decisions.
  • Specialised knowledge and skills required to use contemporary Big Data technologies to store, manage, process and analyse large structured or unstructured data sets.
  • Effective independent and collaborative work skills to apply specialised knowledge and expert judgement to data science.

Details

Information correct as atMar 29, 2024 5:44 pm
Program code40112
AQF level

Level 9 Masters Degree (Coursework)

Locations and UAC codes
Mode of delivery
  • Online
Duration
  • Australian students - 1.5 years full-time or part-time equivalent.
  • International students - 1.5 years full-time.
Term typeSemesters and Trimesters
Fees
Relevant University rules and policies

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Admission information

Admission requirements

  • Students with a three year, Bachelor degree (AQF level 7) or higher in a different discipline area (also called non-cognate discipline) to data science and their chosen specialisation are eligible to undertake the 120 unit program which can be completed in 2 years full time (commencing Semester 1), 1.5 years full time (commencing Semester 2) or up to 5 years part time. 
  • Students with a three year Bachelor degree (AQF level 7) or higher in a non-cognate discipline who also hold a minimum of five years demonstrable Recognised Prior Learning (RPL) in an area related to data science and/or their chosen specialisation (also called cognate discipline) may be eligible to study between 80 and 120 units, inclusive.
  • Students with a three year Bachelor degree (AQF level 7) or Bachelor (Honours) (AQF 8) in a cognate discipline to data science and/or their specialisation may be eligible to study between 80 and 120 units, inclusive.
  • Students with a Graduate Certificate or Graduate Diploma (AQF level 8) in a cognate discipline to data science and/or data analytics may be eligible to undertake an 80 unit program which can be completed in 1 year full time or part time equivalent.

English Language 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.

  • IELTS Overall Minimum: 6.5
  • IELTS Sub Test Minimum: 6

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

120 units

Program duration

1.5 years full-time or part-time equivalent up to 5 years maximum.

Program requirements

Please note that students who commence in Semester 1 can complete the program in a minimum of 2 years full time. Students who commence in Semester 2 can complete the program in a minimum of 1.5 years full time.

Students are required to complete a total of, but no more than, 120 units, comprised of the following:

  • 40 units of Core courses
  • 10 units of courses chosen from the Course List.
  • One 60 unit Specialisation
  • 10 unit Elective

Please note: Students must only complete courses that form part of the program.


Program planner

Current students program planner

Current students can plan their program using Program Planner.

Program Planner

Prospective student degree planner

If you're a prospective student considering studying this degree take a look at My Degree Planner to see what your study journey will look like.

Additional documents


Transition arrangements

2021 Revision

From Semester 2 2021, the Computational Intelligence Specialisation has been updated to remove INFT6304 and SENG6051 as directed courses. Students who are completing this specialisation and commenced prior to Semester 2 2021 can count INFT6304 or SENG6051 as their directed course. Students who commence from Semester 2 2021 cannot count INFT6304 or SENG6051 as their directed course.


Program structure

Students can plan their program using Program Planner. It is recommended students review the program handbook in conjunction with using Program Planner.

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Core

Complete the following core courses to fulfil the requirements of this program.

CodeTitleTerm / Location Units
COMP6140Databases and Information Management
  • Semester 2 - 2024 (Online)
10 units
INFT6201Big Data
  • Trimester 3 - 2024 (Callaghan)
  • Trimester 3 - 2024 (NAIHES)
  • Trimester 3 - 2024 (Online)
  • Trimester 3 - 2024 (Sydney CBD)
10 units
STAT6001Data Wrangling and Visualisation
  • Semester 1 - 2024 (Online)
10 units
STAT6020Predictive Analytics
  • Semester 2 - 2024 (Online)
10 units

Course List

Complete 10 units from the following course list.

CodeTitleTerm / Location Units
STAT6160Data Analytics for Business Intelligence
  • Semester 1 - 2024 (Online)
  • Semester 1 - 2024 (Sydney CBD)
10 units
STAT6170The Science of Data Interrogation
  • Semester 1 - 2024 (Online)
10 units

Specialisation

Computational Intelligence

Compulsory

Complete the following compulsory courses.

CodeTitleTerm / Location Units
COMP6340Data Mining
  • Semester 2 - 2024 (Online)
10 units
COMP6380Machine Intelligence
  • Semester 1 - 2024 (Callaghan)
  • Semester 1 - 2024 (Online)
10 units
COMP6900Computing Project
  • Semester 2 - 2024 (Online)
20 units
INFT6800Professional Practice in IT
  • Trimester 2 - 2024 (Callaghan)
  • Trimester 2 - 2024 (NAIHES)
  • Trimester 2 - 2024 (Online)
  • Trimester 2 - 2024 (Sydney CBD)
10 units
Course List

Complete 10 units from the following course list.

CodeTitleTerm / Location Units
COMP6230Algorithms
  • Semester 2 - 2024 (Callaghan)
10 units
COMP6350Advanced Database
  • Semester 1 - 2024 (Online)
10 units
INFT6009Cloud Computing and Mobile Applications for the Enterprise
  • Trimester 2 - 2024 (Callaghan)
  • Trimester 2 - 2024 (Online)
10 units
SENG6110Object Oriented Programming
  • Trimester 1 - 2024 (Callaghan)
  • Trimester 1 - 2024 (NAIHES)
  • Trimester 1 - 2024 (Online)
  • Trimester 1 - 2024 (Sydney CBD)
10 units
SENG6120Data Structures
  • Semester 1 - 2024 (Callaghan)
  • Semester 1 - 2024 (Online)
10 units

Health Data Analysis

Compulsory

Complete the following compulsory courses.

CodeTitleTerm / Location Units
BIOS6070Linear Regression Modelling
  • Semester 1 - 2024 (Online)
10 units
BIOS6940Generalised Linear Models
  • Semester 1 - 2024 (Online)
10 units
BIOS6990Applied Longitudinal Analysis
  • Semester 2 - 2024 (Online)
10 units
PUBH6303Applied Research
  • Semester 2 - 2024 (Callaghan)
  • Semester 2 - 2024 (Online)
10 units
Course List

Complete 20 units from the following course list.

CodeTitleTerm / Location Units
BIOS6061Clinical Trial Design
  • Semester 2 - 2024 (Online)
10 units
BIOS6170Probability and Biostatistical Inference
  • Semester 2 - 2024 (Online)
10 units
EPID6420Fundamentals of Epidemiology
  • Semester 1 - 2024 (Callaghan)
  • Semester 1 - 2024 (Online)
  • Semester 2 - 2024 (Online)
10 units
EPID6430Advanced Epidemiology
  • Semester 2 - 2024 (Callaghan)
  • Semester 2 - 2024 (Online)
10 units

Electives

Electives 10 unit requirement

Complete 10 units of electives to fulfil the requirements of the program. Electives can be used to extend and complement your core studies with more courses in the same field of study, or from areas that might be of interest to you. Electives can be chosen from all postgraduate courses available at the University that do not have any other conditions (such as a course requisite) applied to them.

10 units

Additional information

Through the Pathways and Academic Learning Support Centre, students can access a free suite of NUPrep preparation courses as well as Academic Learning Support.

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 College 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.