Bachelor of Data Analytics
Transform data into meaningful insight. Become the highly valued professional that helps business make better-informed decisions.
About the Course
Study Data Analytics On Demand with UniSA Online and take full control over your study. Access support seven days a week, plan your study to fit around your life, view learning resources 24/7, and log into the interactive online environment anywhere, any time and on any device.
UniSA Online’s data analytics degree is an opportunity to propel yourself into the booming field of data science. Employers are looking for people who can transform oceans of data into streams of meaningful insights to make better-informed decisions, drive business growth, and increase their competitive advantage. Through extensive industry consultation, we’ve designed a 100% online data analytics degree that covers emerging data trends and the latest developments in the field to ensure you graduate with a hyper-relevant skillset to enter the industry for the first time, or land a higher-level role.
Discover how data can be used to achieve organisational objectives, whether it be through cost reductions, faster and more effective decision making processes, or the development of new products and services.
The flexibility of this 100% online degree puts you in control of when and where you study. UniSA Online provide personalised and extended-hour support so you have the best chance to succeed and thrive in your studies.
Course Entry Requirements
This UniSA Online degree is currently available for Commonwealth supported students.
Applicants are required to fulfil at least one of the following requirements with a competitive result and meet any other academic requirements for the program:
- Successfully completed equivalent to a minimum of half a year of full-time study of a higher education program at a recognised higher education provider
- Completed an award from a registered training organisation at Certificate IV level or above
- Passed a UniSA Online literacy and numeracy test and have relevant work experience
- Completed a secondary education qualification equivalent to SACE, such as an interstate year 12 or international qualification
- Completed a UniSA Foundation Studies Program or equivalent
- Qualified for Special Entry
Course Structure
Recommended study pattern
Note: The program structure is subject to change at any time. Information correct as at March 2023.
Year 1
- Professional Practice in Data Analytics (INFS 1028)
- Information Technology Fundamentals (INFT 1024)
- Fundamentals of Mathematics for Data Analytics (MATH 1080)
- Problem Solving and Programming (COMP 1043)
- R for Data Analytics (MATH 2032)
- Data Driven Web Technologies (INFT 1032)
- Object Oriented Programming (COMP 1048)
- Elective 1
Year 2
- Mathematics Essentials in Data Analytics (MATH 1081)
- Data Acquisition and Wrangling (INFT 2067)
- Cloud Platforms (INFT 2066)
- Applied Data Structures (COMP 2033)
- Database for the Enterprise (INFT 2068)
- System Requirements and User Experience (INFS 1029)
- Data Visualisation (INFS 3080)
- Predictive Analytics (INFS 3081)
Year 3
- Experimental Design (INFS 2049)
- Big Data in the Cloud (INFS 3088)
- Text and Social Media Analytics (INFS 3089)
- Elective 2
- Capstone Project 1 (INFT 3039)
- Machine Learning (INFT 3046)
- Capstone Project 2 (INFT 3040)
- Advanced Topics in Data Analytics (INFS 3087)
Award requirements
Students must complete 24 subjects, this includes 2 electives.
Demand for data analysts is soaring, but there is a widening gap between the needs of organisations and the abilities of job candidates to fulfil those needs. Your UniSA Online data analytics degree is an opportunity to equip yourself with a powerful skill set that will make you highly competitive in the marketplace.
You'll learn to:
- Analyse and visualise rich data sources and identify data trends, as well as generate data management strategies.
- Perform predictive analytics on big data sets and become fluent in R and Python.
- Use data visualisation tools as well as programs and techniques for data acquisition and data cleaning.
- Explore emerging topics such as cloud computing, machine learning, artificial intelligence, and text and social analytics.
You'll also have access to data analytics software and tools used by industry professionals for free.
