ITO5149 Applied data analysis
Faculty of Information Technology
ITO5149 Applied data analysis is a level 5, 6-credit-point, postgraduate unit from the Faculty of Information Technology. It isn't offered in 2027. It needs ITO5197.
- Credit points
- 6
- Offered in 2027
- Other periods
- Monash Online
- Assessment
- No exam
- 2 tasks
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Requisites
Before ITO5149
Prohibitions
You can't enrol if you have passed any of these.
Prerequisites
Pass these before you enrol.
After ITO5149
No unit lists ITO5149 as a prerequisite in the 2027 handbook.
Equivalent units
The same content under another code. Only one of them counts.
Overview
This unit aims to provide you with the necessary analytical and data modelling skills for the roles of a data scientist or business analyst. You will be introduced to established and contemporary Machine Learning techniques for data analysis and presentation using widely available analysis software. You will look at a number of characteristic problems/data sets and analyse them with appropriate machine learning and statistical algorithms. Those algorithms include regression, classification, clustering and so on. The unit focuses on understanding the analytical problems, machine learning models, and the basic modelling theory. You will need to interpret the results and the suitability of the algorithms.
Offerings in 2027
| Teaching period | Campus | Mode |
|---|---|---|
| Teaching period 6 | Monash Online | Mo |
Assessment
- Assignment 1 Basic regression analysis and classificationProject40%
- Assessment 2 Data analysis challengeProject60%
Assessment details may change. Please refer to the assessment information in Moodle closer to the start of the teaching period.
Learning outcomes
When you finish this unit, you should be able to:
- 1
Analyse data sets with a range of statistical, graphical and machine-learning tools;
- 2
Evaluate the limitations, appropriateness and benefits of data analytics methods for given tasks;
- 3
Design solutions to real world problems with data analytics techniques;
- 4
Assess the results of an analysis;
- 5
Communicate the results of an analysis for both specific and broad audiences.
Workload and teaching
- Workshops12 hours
- Teaching approachOnline learning
A minimum of 144 hours over the 6 week teaching period should be used to complete assignments, participating in discussions, private study and revision.
Learning resources
Required resources
James, G., Witten, D., Hastie, T., & Tibshirani, R. (2013). An introduction to statistical learning
Zhao, Y (2012) R and Data Mining: Examples and Case Studies. Academic Press
Technology resources
Students will need R/Python, which is freely available software that can be download from the Internet.
Contacts
- Chief Examiners
- Dr Lizhen Qu
Common questions
What are the prerequisites for ITO5149?
You need ITO5197 before you enrol.
When is ITO5149 offered?
ITO5149 has no offerings listed in the 2027 handbook.
Does ITO5149 have an exam?
No. ITO5149 has 2 assessment tasks and no exam.