Charles Sturt University
Graduate Certificate of Data Science
- Delivery: Online
- Study Level: Postgraduate
- Duration: 6 months
- Course Type: Graduate Certificate
Explore applied data science through postgraduate study, developing practical skills in big data analytics, statistical methods and data-driven techniques to extract insights from raw data.
Course overview
The Graduate Certificate in Applied Data Science from Charles Sturt University is a specialised postgraduate program designed to advance knowledge and skills in the field of data science. Completed over 0.5 years full-time or equivalent part-time, the course provides an overview of current information technology trends and techniques used to extract knowledge and insights from raw data.
Throughout the course, you will explore the foundations of big data analytics and develop skills in analysing data through statistical and programming approaches. The program covers contemporary data analytics areas including data mining, machine learning, scientific statistics and knowledge engineering, allowing you to examine how these techniques can be applied to solve real-world data analytic problems.
The course also provides practical hands-on experience using data analytics software platforms commonly utilised within industry. With flexible elective options across areas such as artificial intelligence and machine learning, database systems, programming principles and advanced statistical analysis, the course allows you to develop knowledge aligned with your interests in applied data science. Successful completion may provide a pathway into the Master of Information Technology with credit for applicable subjects.
Key facts
12th July, 2027
What you will study
To earn the Graduate Certificate of Applied Data Science, you must successfully complete units totalling 32 credit points, as detailed below. Unless otherwise noted, each course is worth 8 credit points.
Core Units
- Foundations of Big Data Analytics
Elective units
Select 24 credit points from the following:
- Data Mining and Visualisation for Business Intelligence
- Database Systems
- Programming Principles
- Internet of Things
- Data and Knowledge Engineering
- Artificial Intelligence and Machine Learning
- Advanced Statistical Modelling
- Multivariate Statistical Analysis
- Scientific Data Analysis
- Experimental Design and Analysis (PG)
Entry requirements
Academic requirements
Applicants for this course must meet one of the following:
- Bachelor's degree from a recognised tertiary institution.
- Two years relevant work experience.
- Graduate Certificate in a related area.
Language requirements
Standard English Language Proficiency (ELP) requirements apply. Contact the university or visit their website for more information.
Recognition of Prior Learning
You may be eligible for recognition of prior learning if you have previously studied or have relevant work experience. This will help reduce the number of units you need to study to finish your course. Contact the university for more information.
Outcomes
Learning outcomes
Upon completion of this course, graduates will be able to:
- Investigate and analyse the core requirements of big data analytics in the context of information technology.
- Apply suitable statistical and programming skills to solve real-world data analytic problems.
- Demonstrate through critique and application, a knowledge of current data analytics trends such as data mining, machine learning, scientific statistics and knowledge engineering.
Career outcomes
The Graduate Certificate in Applied Data Science is designed for professionals who want to develop their knowledge and practical skills in the field of data science. The applications for data science continue to expand across many industries – whether you are interested in using data analytics to extract insights from raw data, support decision-making through data analysis, or explore emerging technologies such as machine learning and artificial intelligence.
With practical skills and knowledge of current data analytics techniques, you can apply your capabilities in roles such as data analyst, data scientist, data architect or enterprise data architect, depending on your professional goals and experience.
Fees and FEE-HELP
Indicative annual fee in 2026: $17,480 (Full-fee paying place)
Indicative annual fees are based on your first year of study.
A student’s annual fee may vary by:
- The number of units studied.
- Choice of units.
- Credit from previous study or work experience.
- Eligibility for government-funded loans.
Student fees shown are subject to change. Contact the university directly to confirm.
FEE-HELP loans are available to assist eligible full-fee paying domestic students with the cost of a university course.