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Develop your skills before you commit to a full degree

Studying a single unit in data science with Monash Online equips you with the latest knowledge in managing, analysing, and visualising data in just six weeks. Handpick your preferred data science units, with access to the curriculum delivered and assessed by our academic staff.

Why Monash Online single units?

  • Flexible – Offered 100% online and taught in six weeks
  • Credit-bearing – May be used as credit for those considering a Graduate Diploma of Data Science
  • Credible – Learn from Monash’s leading academic staff and researchers
  • Hands-on support – Dedicated Student Success Advisor guiding you through your studies
  • Postgraduate curriculum – Derived from Monash Online’s Graduate Diploma of Data Science

For more information call us on 1300 057 347 or book in a time to speak to an Advisor today. 


If you have a background in programming and databases and want to evolve into a new role in data science, this foundational unit can be your first step.

  • FIT5145: Introduction to data science
    This unit explores the many facets of working with data. It includes the handling of data, styles of data analysis, working with data as part of a business model and reviewing case studies of successful data analysis and exploration.


Delve into data analysis and program design with the professional skills of a data scientist. Programming units focus on: solving problems with programs like Python; machine learning; data visualisation; and data modelling.

  • FIT5197: Modelling for data analysis
    This unit explores basic probability distributions, random number generation, and estimation methods. It reviews the statistical modelling foundations that underlie the analytics aspects of data science.
  • FIT5201: Machine learning
    This unit introduces machine learning and the major kinds of statistical learning models and algorithms used in data analysis. You’ll be presented with foundational concepts in machine learning and statistical learning theory, and how model complexity interplays with a model’s performance on unobserved data.
  • FIT5147: Data exploration and visualisation
    This unit introduces statistical and visualisation techniques for the exploratory analysis of data. It covers the role and limitations of data visualisation, the visualisation of qualitative, quantitative, temporal and spatial data and creating effective data visualisations with R.
  • FIT9133: Programming foundations in Python
    This unit introduces you to program design and the Python language. You’ll learn ways of using algorithms to solve computational problems.
  • FIT5149: Applied data analysis
    This unit will give you the analytical and data modelling skills you’ll need to be a data scientist or business analyst. You’ll be introduced to various data analysis techniques and learn how to use them to address characteristic problems.



The effective management of databases is vital to both small businesses and large enterprises. Our short database units give you a deeper understanding of the inner workings of a database, and how to manage large data with technology, software tools and techniques.

  • FIT9132: Introduction to databases
    This unit reviews organisational data management through relational database technology, including relational model analysis and design.
  • FIT5202: Data processing for big data
    This unit teaches about working with different kinds of data, documents, graphs, and spatial data. Distributed processing is introduced using Hadoop and Spark technologies, including streaming, graph processing and using NoSQL. Programming assignments are generally done in Spark, Linux, and similar shell-like environments.
  • FIT5148: Big data management and processing
    This unit introduces the software tools and techniques for data engineering. It covers traditional methods of data processing, introduction to distributed databases, and the handling and processing of big data.
  • FIT5196: Data wrangling
    In this unit, you’ll develop the skills required to prepare raw data for analytics, including data cleansing and pre-processing. Python and the Pandas environment will be used as part of this course.


Maths and stats

The core of data science is a long sequence of numbers and algorithms. Maths and stats are the basis of this field and you will need to be an expert in numbers.

  • MAT9004: Mathematical foundations for data science
    This unit includes the mathematical topics fundamental to data science, computing and statistics, including linear algebra, trees and other graphs, principles of elementary probability theory, fundamental concepts of calculus in one and several variables and counting in combinatorics.


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