Discover 12 top online data analysis courses in Australia for exciting career opportunities in this growth field. Learn AI, business analytics, data science, and more.
Data analytics training is the foundation for a career in data-driven decision making. Analysts bring expertise in technology, statistics and business together to extract value from data assets. Here are the best types of university courses.
Types Of Courses
Data Analysis Courses
University courses for data analysts include bachelor degrees, graduate certificates, graduate diplomas, and masters. They cover data analytics, data science, AI management, and business analytics, with varying levels of technical and business skills required. Online courses are flexible, allowing you to customise your learning experience.
You can major in data science and analytics in a bachelor degree. Typically, a data major is available within computer science or IT undergraduate programs.
A bachelor course will teach you important core skills and set up your career. Almost every analyst and data scientist around has a bachelor degree of some kind, usually in a technology field.
Most programs are flexible and allow you to adjust your study direction from year to year. You can also combine disciplines. Students often complement data analysis or data science with business or maths studies… READ MORE
An important and growing way of using data is to produce artificial intelligence or AI. You can learn the fundamentals of harnessing the potential of AI with a Graduate Certificate in Artificial Intelligence Management.
Knowing when and how to solve a business problem using AI starts with understanding data analysis. You can then deploy machine learning to generate artificial intelligence.
A graduate certificate course could provide early mover advantages for managers with technical aptitude. You'll be able to grasp AI opportunities that competitors may overlook or struggle to implement... READ MORE
A Graduate Certificate in Business Analytics is a postgraduate course designed to develop skills in business analysis. Students learn to use data and technology to understand what happened, why it happened, and what to do next.
The program contains four subjects, which can be chosen to meet learning goals. Graduates are able to synthesise data, perform descriptive, predictive, and prescriptive analytics, and use data to recommend business solutions.
Career opportunities in this field include business analyst, data analyst, HR analyst, market analyst, and digital marketing analyst.… READ MORE
A Graduate Certificate in Data Analytics is a 4-subject course providing (a) foundation studies in data analysis (b) advanced training in chosen subjects or (c) a combination of introductory and advanced units.
Students often enroll part-time in a grad cert course to gain entry into a masters program. They might continue beyond the course, to go for an 8-subject graduate diploma or 12-subject masters, if the learning experience is a good one.
A data analyst course may be open to graduates (any bachelor degree) or professionals with relevant experience. You need strong math ability to do well… READ MORE
A data science graduate certificate is a 4-subject course normally embedded within a masters program. It introduces foundational topics and may contain units that are prerequisites for advanced studies.
A grad cert in data science is often a pathway course. Significant further training, either within the masters program or outside, should follow to develop the advanced programming skills that data science requires.
To be admitted, you need a relevant technology or business degree or, alternatively, professional experience as a data analyst or data scientist… READ MORE
Halfway in duration between a graduate certificate and masters, a Graduate Diploma in Analytics may be just the right course for you. Consisting of 8 subjects, you can finish a graduate diploma over 16 months of part-time study.
An advantage of this type of program is that you can take a deep dive exclusively into the topics that interest you. Skip those subjects from the master's degree that you feel carry least value for you.
An "Analytics" program allows you to specialise in data analytics, business analytics or a combination of these overlapping disciplines… READ MORE
A cool late-stage application of data analytics is to produce artificial intelligence or AI. You can learn when and how to generate AI with a Masters in AI Management program.
An AI management program is a technology course with low to moderate technical content. You should have analytics aptitude and be willing to dive into technical content as required. But, ultimately, you're developing an ability to initiate and manage AI projects.
You can study other topics as part of the program, including foundational units on data analysis and machine learning... READ MORE
A masters degree in analytics allows you to develop the breadth of skills required to excel as a data analyst.
Job opportunities in the data analysis field vary greatly in terms of the technical and business skills that are called upon. A master's is a great way to extend your capabilities and always be in high demand.
Masters degrees go by different titles, including Master of Analytics, Master of Business Analytics, and Master of Data Analytics. Most programs are 12 subjects long but also allow you to start (and potentially finish) with a 4-subject graduate certificate course… READ MORE
A Masters in Business Analysis is a data analysis program that you can expect to be free of the heavy programming you might find in a data science course. As well, there should be plenty of opportunity to learn how to apply data analytics to decision-making in business.
Examples of subjects in a business analysis masters are accounting practice and tools, delivering customer value, machine learning, data processing, and financial analytics.
Demand for business analysts is high across Australian industries, with companies wanting to exploit burgeoning volumes of commercial data… READ MORE
A master's degree in data science is a powerful way to start or boost a career in the boom field of big data. Students gain better foundation training than the majority of current data scientists.
Career opportunities abound for people with the maths and coding talent to generate business value from information assets.
An IT background is highly advantageous for postgraduate courses. Students can do a masters (12+ subjects), graduate diploma (8 subjects) or a graduate certificate (4 subjects)… READ MORE
Marketing is fertile field for data analysis. You can use analytics to help find potential customers, quantify the effectiveness of marketing campaigns, adapt your messaging based on customer responses, and so forth.
With marketing being a vital business function, demand is high for marketing analytics professionals. You can develop and demonstrate your ability to interpret data with a Masters in Marketing Analytics.
To specialise in marketing, study topics such as customer analytics, social media and digital analytics alongside generic data analysis subjects… READ MORE
One of the least technical master's degrees in the field is an MBA in Data Analytics. The course develops your management and leadership skills while imparting knowledge for working with data.
Managers need data analysis skills if for no other reason than to better interpret analytics presented to them. But there is also the potential to commission, lead or supervise data-orientated projects.
A Data Analytics MBA is highly relevant to many careers in business given the growing significance of analytics in decision making... READ MORE
Why These Programs Are Worthwhile
Doing a data analysis course is worth it. With increasing amounts of data being generated, the demand for analytical skills is rising. Studying online gives you access to job-relevant courses with high potential returns.
Universities in Australia offer a range of online postgraduate courses to improve your analytical skills, from graduate certificates to masters degrees. It is recommended that you start with a graduate certificate, which is a shorter course and pathway to further study if you wish.
There are good reasons to learn data analytics. You can enter into a rewarding profession, qualify for more jobs, boost your salary, access professional resources, and receive comprehensive, structured training. The value of the opportunities created can easily exceed your study costs.
Programs may cover core topics such as data handling, analysis techniques, visualisation and communication. Aside from that, the structure tends to vary depending on whether data science and programming are emphasised or business analytics.
Course duration is 16 subjects (including electives) for a bachelor degree, 12 typically for a masters and 4 for a graduate certificate. Here are example subject lists.
- Introductory Data Science
- Ethics and Data Management
- Data Analytics
- Mathematics for Data Science
- Visual Basic and Excel Programming
- Data Handling and Visualisation
- Statistical Inference & Machine Learning
- Advanced Data Analysis
- Principles of Programming
- Introductory Data Analysis
- Analytics and Business
- Managing People, Analytics and Change
- Big Data Management
- Data Visualisation and Communication
- Predictive Analytics
- Data and Ethics
You should come away from an analytics course with confidence in your ability to extract meaning and value from data sets. For a longer program, learning outcomes may include the ability to do the following.
- Apply data analysis to inform decision making about strategy, customers and services.
- Assess the potential statistical uses of industry data sets for business intelligence.
- Build predictive models to analyse data and inform business decisions.
- Create effective data visualisation and storytelling using R and Tableau and other tools.
- Demonstrate expertise on Big Data storage, databases, manipulation, and applications.
- Demonstrate technical understanding of tools and methods used in data science.
- Explain how programming can, along with testing and debugging, be used to analyse data.
- Explain machine learning methods and develop strategies for data mining and computing statistics.
- Select and apply analytical methods and tools to data sets, including for qualitative analysis.
Graduates know analytical tools, programming languages, data science techniques, how big data is handled, and how to communicate findings visually.
While admission standards vary, typical entry requirements could be summarised as follows.
- Free online data analysis course: None
- Bachelor degree: A sufficient ATAR score, with mathematics subject achievement
- Graduate certificate: A bachelor degree or relevant experience
- Master's degree: A bachelor degree, with solid grades and/or in a relevant discipline.
To do well, you generally need mathematical aptitude. Some postgraduate programs make this an entry requirement while others don't, instead allowing applicants to use their own judgement about their suitability.
Data analytics requires coding but is not as coding-intensive as fields such as data science and computer science. Some aspects of being a data analyst require you to write code. But you can accomplish many of the tasks with moderate programming skills and by learning specific languages and algorithms on-the-job.
Degree courses are fairly light on in terms of the amount of coding content.
- A bachelor's degree may require little more than learning Visual Basic and Excel programming, which is coding within a spreadsheet platform.
- A master's program may extend into Python (an intuitive program for writing algorithms), SAS (which handles database manipulations), SQL (for database queries) and R (for statistical analysis and presentation).
Graduate jobs for data analysts generally don't require advanced programming skills. Employers expect you to be willing to learn coding as required but there are many other aspects to the work. To prepare for a career in this field, you should experiment with different programming languages and gain some familiarity with the main ones. But you don't have to be an expert in any given language or platform.
To become a fully qualified data analyst, you can complete a Bachelor of Data Analytics (or similar) in 3 years of full-time study in Australia. If you already have a degree, a Master of Data Analytics is a 1.5 year program. An accelerated master's takes 2 years of part-time study online.
You can measure also program duration by the number of subjects. Full-time on-campus students complete four subjects each semester, or 8 subjects per year. Online students in accelerated programs complete one subject every 2 months.
- Bachelor degree: 24 subjects (3 years full-time)
- Graduate certificate: 4 subjects (8 months part-time online)
- Graduate diploma: 8 subjects (16 months part-time online)
- Master's degree: 12 subjects (2 years part-time online)
An online university degree such as a bachelor degree or master's degree in Data Analytics provides a well-rounded education. Shorter online postgraduate courses, namely graduate certificates and diplomas, offer foundational or specialised training.
Accelerated online courses are ideal for busy professionals. You can study fully online at times convenient for you. The programs are designed for part-time study, with online students only asked to focus on one subject at a time.
Once you've made a start to your career, you can do short courses to develop skills in targeted areas. You can search for short courses online by the target subject, such as Tableau, SQL, business intelligence, Python, data analytics for business, tools to interpret data, processing raw data, etc.