The Graduate Diploma of Data Science will prepare you for a career in data science giving you the skills needed to deal effectively within the areas of data analysis, data management or big data processing. The course includes topics in statistical and exploratory analysis, data formats and languages, processing of massive data sets, management of data and its role and impact in an organisation and society.
Postgraduate - Course
This course entry applies to students commencing this course in 2018 and should be read in conjunction with information provided in the 'Faculty information' section of this Handbook by the Information Technology.
Unit codes that are not linked to their entry in the Handbook are not available for study in the current year.
Admission and fees
1.4 years PT
You have a maximum of four years to complete this course.
Mode and location
Online (Monash Online)
This course is taught online.
Graduate Diploma of Data Science
Graduate Certificate of Data Science
Refer to 'Alternative exits' entry below for further requirements and details.
This course is not available to international students who are holders of an Australian student visa, for study onshore in Australia. However holders of some other categories of Australian visas living in Australia, and students studying off-campus by distance learning (where this option is available) and living outside of Australia, may be eligible for this course.
These course outcomes are aligned with the Australian Qualifications Framework level 8 and Monash Graduate AttributesAustralian Qualifications Framework level 8 and Monash Graduate Attributes (http://www.monash.edu.au/pubs/handbooks/alignmentofoutcomes.html).
Upon successful completion of this course it is expected that you will be able to:
- analyse the lifecycle of data through an organisation
- apply the major theories in the field of data analysis and data exploration to some characteristic problems
- investigate, analyse, document and communicate the core issues and requirements in developing data analysis capability in a global organisation
- demonstrate an understanding of data science to a level of depth and sophistication consistent with senior professional practice
- review and evaluate data science projects
- document and communicate ethical and legal issues and norms in privacy and security, and other areas of community impact with regards to the practice of data science.
This course consists of eight units. You complete core studies in introductory data science, data wrangling and modelling for data analysis, then select units from across a range of areas where you can tailor the course to suit your own interests. Your choice of units covers studies in data exploration and visualisation, distributed and big data processing and data analysis and data management.
If you do not meet course requirements in programming, databases or mathematics/statistics, you must complete up to two foundation units prior to commencing your core studies.
The course comprises 48 points.
Units are 6 credit points unless otherwise stated.
You must complete:
a. up to two foundation units (0-12 points)
- Programming foundations in Python
- Introduction to databases
- Mathematical foundations for data science
b. three core units (18 points):
- Introduction to data science
- Data wrangling
- Modelling for data analysis
c. three to five units (18-30 points) selected from:
- Data curation and management
- Data exploration and visualisation
- Distributed databases and big data
- Applied data analysis
- Data analysis algorithms
- Data processing for big data
You may exit this course early and apply to graduate with the following award, provided you have satisfied the requirements indicated for that award during your enrolment in this diploma course:
- Graduate Certificate of Data Science after successful completion of 24 credit points of study, including FIT5145, FIT5196, and FIT5197 and one 6-point unit from a. or c.
Progression to further studies
This course provides a pathway to the master's by coursework degree, C6004 Master of Data Science.