Graduate Diploma in Data Science

To do this course, you’ll need:

• A recognised bachelor’s degree (or equivalent qualification) in a non-cognate discipline AND have sufficient Data Science background as indicated by an average of 65 or above across three Level III courses in Mathematics and/or Statistics and/or Computer Science and/or Econometrics; OR
• A recognised bachelor’s degree (or equivalent qualification) in a non-cognate discipline AND have sufficient Data Science background as indicated by at least five years of experience in a data science or data analytics role; AND
• To be proficient in the English language.

Entry via nested qualification 

• If you have completed a Graduate Certificate in Data Science with a WAM of 65% or higher as per the UNSW Admissions entry calculator, you can progress to the Graduate Diploma in Data Science.  

The Graduate Diploma in Data Science comprises eight online subjects. Completing these courses will provide you with a comprehensive understanding of Data Science, and the practices crucial to decision-making techniques and good data storytelling.

Core subjects (six total):

• Principles of Programming
• Foundations of Data Science
• Statistical Inference for Data Scientists
• Data Mining and Machine Learning
• Regression Analysis for Data Scientists
• One of: Strategic Decision Making or Database Systems

Elective subjects (choose two provided the prerequisites are met and subjects are available):

• Big Data Management
• Data Visualisation and Communication
• Multivariate Analysis for Data Scientists
• Neural Networks, Deep Learning
• Bayesian Inference and Computation
• Decision Making in Analytics
• Data and Ethics
• Strategic Decision Making (if not chosen as core subject)
• Database Systems (if not chosen as core subject)

Should you choose to pursue Master of Data Science upon the successful completion of your Graduate Diploma, the following prerequisites must be considered: 

• Principles of Programming is a prerequisite for Data Mining & Machine Learning, Neural Networks, Deep Learning & Big Data Management.
• Foundations of Data Science is a prerequisite for Regression Analysis for Data Scientists, Data Visualisation and Communication & Multivariate Analysis for Data Scientists.
• Statistical Inference for Data Scientists is a prerequisite for Regression Analysis for Data Scientists & Multivariate Analysis for Data Scientists.