Enrolments: 302,530

Master Degree and Graduate Certificate Course Enrolments: 7,138

The total number of Master degree and Graduate Certificate enrolments since Charles Sturt University and IT Masters launched our first qualification in 2003.

Short Course Enrolments: 295,392

The total number of enrolments in our free short courses that we offer as a ‘taster’ of what it is like to study via Distance Education with Charles Sturt University.

Free Short Course: Introduction to Knowledge Discovery and Data Mining

This short course will help you to understand some data mining techniques for knowledge discovery and knowledge presentation. At the end of the short course you should be able to use the skill for knowledge discovery and future prediction from a suitable dataset of your interest.

This short course is also a taster of the Graduate Certificate in Applied Data Science course at CSU.

Find out more in this free short course!

Difficulty
■■■■ Intermediate
More Info
Moderate-level short course where some prior knowledge or concepts may be assumed. Content may be aimed at late-undergraduate or early-Masters students
Duration4 Weeks
Enrolled2,313 students
CostFree!

Enter your details below to register:

Course Schedule

Module 1:

Introduction to Data Mining

 
  • Data Life Cycle
  • Data types, collection and pre-processing
  • Data Analysis: supervised and unsupervised learning

Webinar: Tuesday 5th November 7:30pm AEDT

Module 2:

Decision Tree Classifiers

 
  • Decision Trees
  • Usefulness of decision trees
  • Limitations of decision trees
  • Ensemble of trees

Webinar: Tuesday 12th November 7:30pm AEDT

Module 3:

Knowledge Discovery

 
  • Knowledge Discovery Techniques
  • Knowledge Interestingness Measures
  • Case Study

Webinar: Tuesday 19th November 7:30pm AEDT

Module 4:

Decision Support System (DSS)

 
  • Overview of a DSS
  • Architecture and Types of DSS
  • Requirements of a DSS
  • Case Study

Webinar: Tuesday 26th November 7:30pm AEDT

Assessment:

Examination

 
  • Exam pass mark: 50%
  • Time limit: 30 minutes
  • Attempts allowed: one
  • Format: 20 multiple choice questions

Course Information Q&A

What will I learn in this short course?

This short course should help you to understand some data mining and knowledge discovery techniques. After completing the course, you should be able to apply this skill on suitable datasets and the skill obtained should help you to contribute more in the data analysis and decision-making process at your workplace.

What is the aim of this short course?

This aim of this short course is to give you a taste of what it is like to study the Graduate Certificate in Applied Data Science course at Charles Sturt University.

How much demand is there for Data Science related jobs?

We’re creating more than 2.5 exabytes of data every day and knowledge discovery from this data is crucial for the organisation to get competitive advantages. As a result, Linkedin rated data science related jobs as the most promising jobs in 2019 and the Harvard Business Review described Data Scientist as the Sexiest Job of the 21st Century.

Who will present the webinars?

This course will be delivered by Associate Professor Zahid Islam and Dr Michael Bewong. Zahid is the Director the Data Science Research Unit (DSRU) at Charles Sturt University. He has so far published 100 peer reviewed papers attracting more than 1250 citations. Along with other colleagues, he also completed many projects funded by various industry partners. One of his projects funded by the NSW Health received the Innovation Award in 2017 from the NSW Agency for Clinical Innovation. Another project funded by the Department of Social Services was independently reviewed by Deloitte and received an “outstanding” feedback from the assessment team. He has also served in various roles including the Conference Chair for the 16th Australasian Data Mining conference in 2018.

Zahid has wide range of qualifications including:

  • PhD in Computer Science from the University of Newcastle Australia.
  • Graduate Diploma in Information Science from the University of New South Wales, Australia.
  • Bachelor in Engineering from the Rajshahi University of Engineering and Technology, Bangladesh.

Michael Bewong is a Lecturer in Computing at Charles Sturt University. He has worked on various industry funded data science projects in the areas of social media analytics and cybersecurity. Particularly, he has developed novel machine learning models for predicting socially disruptive events as well as exploits of cybersecurity vulnerabilities from social media data. Michael has also developed several privacy preserving publication algorithms which preserve the privacy of individuals’ data within a dataset without diminishing its data mining utility. These have been published at top ranking conferences and journals.  He has also served as a reviewer for several top data mining conferences and journals including TKDE, KDD, WSDM, SDM. He is currently the sponsorship chair for the 17th Australasian Data Mining Conference to be held in December 2019.

Michael obtained a PhD in Computer and Information Science from the University of South Australia, and a BSc (Hons) in Electrical and Electronic Engineering from the University of Mines and Technology, Ghana.

Is there a final exam?

Yes — the short course exam will be a timed, open book exam that you will sit at your computer.

Do I get a completion certificate if I complete the course?

Yes — provided you receive a pass mark (50% or over) for course assessment, which comprises the exam and any available participation marks.

Will I need to purchase any study materials to complete the course?

No — all essential materials will be supplied.

Will the webinars be recorded?

Yes — all webinars are recorded and you will be able to access them, and all other free course materials, by registering for the course.

Will the course qualify me for university credit?

Completion of this short course will not qualify for credit into the Charles Sturt University degrees featured on this website.

If you would like more information on our credit program, please see our information page here.