Data Visualization
Undergraduate
LTU-CSE2DV 2025Course information for 2025 intake View information for 2024 course intake
- Study method
- 100% online
- Assessments
- Subject may require attendance
- Enrol by
- 20 July 2025
- Entry requirements
- Prior study needed
- Duration
- 12 weeks
- Price from
- $1,164
- Upfront cost
- $0
- Loan available
- HECS-HELP and FEE-HELP available
Data Visualization
About this subject
On successful completion you will be able to:
- Write code to clean and format data in preparation for data visualisation.
- Design appropriate and effective visualisations that help users gain deep insight into complex the data sets.
- Create interactive data visualisations for all users to effectively explore the data.
- Generate informative reports using data visualisations.
- Working with Data: From Discovery to Visualisation
- Choosing Appropriate Techniques for Data Visualisation
- Creating Data Visualisations with Tableau
- Creating Data Visualisations with Python
- Information Design
The ability to visualise data is one of the most useful forms of data analysis and data presentation. Data visualisation provides an accessible way to see and understand trends, outliers and patterns in data. Nowadays there are many different tools for collecting and querying data. In order to gain full benefit from the collected data we need to visualise the data. In this subject you will learn the following: how to prepare data for visualisation; the design principals for creating effective data visualisations; and how to communicate your data analysis using reports containing data visualisations. You will learn how to use state of the art software tools for generating insightful and interactive data visualisations.
- Programming assignment 1 (1000 words equivalent) (25%)
- Programming assignment 2 (1000 words equivalent) (25%)
- End of semester examination (2000 words equivalent) (50%)
For textbook details check your university's handbook, website or learning management system (LMS).
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Entry requirements
Prior study
You must either have successfully completed the following subject(s) before starting this subject, or currently be enrolled in the following subject(s) in a prior study period; or enrol in the following subject(s) to study prior to this subject:
Please note that your enrolment in this subject is conditional on successful completion of these prerequisite subject(s). If you study the prerequisite subject(s) in the study period immediately prior to studying this subject, your result for the prerequisite subject(s) will not be finalised prior to the close of enrolment. In this situation, should you not complete your prerequisite subject(s) successfully you should not continue with your enrolment in this subject. If you are currently enrolled in the prerequisite subject(s) and believe you may not complete these all successfully, it is your responsibility to reschedule your study of this subject to give you time to re-attempt the prerequisite subject(s).
Others
Past La Trobe University students who have previously completed CSE2MLX (Machine Learning) are ineligible to enrol in this subject.
Additional requirements
No additional requirements
Study load
- 0.125 EFTSL
- This is in the range of 10 to 12 hours of study each week.
Equivalent full time study load (EFTSL) is one way to calculate your study load. One (1.0) EFTSL is equivalent to a full-time study load for one year.
Find out more information on Commonwealth Loans to understand what this means to your eligibility for financial support.
What to study next?
Once you’ve completed this subject it can be credited towards one of the following courses
Bachelor of Arts/Bachelor of Health Sciences
Undergraduate
LAT-AHS-DEGUndergraduate
LAT-ART-DEGUndergraduate
LAT-HSC-DEGUndergraduate
LAT-BUS-DEGBachelor of Information Technology
Undergraduate
LAT-TEC-DEGBachelor of Psychological Science
Undergraduate
LAT-PYS-DEGUndergraduate
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