Overview
The Master of Data Science (MC-DATASC) program is structured around four specialisations:
- Foundational Data Science specialisation
- Statistical Data Science specialisation
- Computational Data Science specialisation
- Computational and Statistical Data Science specialisation.
Each specialisation has unique requirements and focuses on different aspects of data science. While the specialisations provide focus and advanced knowledge in different areas of data science, all students will have acquired the knowledge covered by the foundational, core and capstone subjects by the completion of the Master of Data Science.
As the Master of Data Science is tailored to students’ backgrounds, it aims to allow students to acquire new knowledge by identifying and recognising subjects that have already been completed through previous study. Where appropriate, these subjects may be converted into non-credit exemptions and replaced with subjects from a specialisation, or from the general and internship subject options.
Specialisation requirements
The main difference between the specialisations lies in the number and focus of elective subjects. Each specialisation allows students to develop deeper expertise in specifically defined areas of data science.
-
This specialisation requires students to complete:
- 50 credit points of Statistics Foundation subjects
- 50 credit points of Computer Science Foundation subjects
- 75 credit points of Core subjects
- 25 credit points of Capstone subjects.
Within this specialisation, students may also complete one specialisation subject, or one general or internship subject, if a University of Melbourne academic expert has identified and recognised that they have completed the equivalent of one Foundation subject through previous study and have been granted a 12.5 credit point non-credit exemption. In this case, they will complete 87.5 credit points of Foundation subjects.
At the completion of the Master of Data Science, students will have acquired the knowledge covered by the Foundation subjects, Core subjects and Capstone subjects, and may also have completed one specialisation, general or internship subject.
-
This specialisation requires students to complete:
- Up to 75 credit points of Statistics and Computer Science Foundation subjects, representing the remaining Foundation subjects that have been identified as not having been completed through previous study,
- 75 credit points of Core subjects
- 25 credit points of Capstone subjects.
Within this specialisation, students deepen their knowledge of statistics and machine learning by completing at least one Statistics Core Discipline subject and one Statistics Discipline subject.
At the completion of the Master of Data Science, students will have acquired the knowledge covered by the Foundation, Core and Capstone subjects. They will also have completed selected statistical specialisation subjects that deepen their knowledge of statistics and machine learning, and may have completed additional specialisation, general or internship subjects.
-
This specialisation requires students to complete:
- Up to 75 credit points of Statistics and Computer Science Foundation subjects, representing the remaining Foundation subjects that have been identified as not having been completed through previous study
- 75 credit points of Core subjects
- 25 credit points of Capstone subjects.
Within this specialisation, students deepen their knowledge of computer science by completing at least one Computer Science Core Discipline subject and one Computer Science Discipline subject.
At the completion of the Master of Data Science, students will have acquired the knowledge covered by the Foundation, Core and Capstone subjects. They will also have completed selected computer science specialisation subjects that deepen their knowledge of computer science, and may have completed additional specialisation, general or internship subjects.
-
This specialisation requires students to complete:
- Up to 50 credit points of Statistics and Computer Science Foundation subjects, representing the remaining Foundation subjects that have been identified as not having been completed through previous study
- 75 credit points of Core subjects
- 25 credit points of Capstone subjects.
Within this specialisation, students deepen their knowledge of statistics, machine learning and computer science by completing at least one Statistics Core Discipline subject, one Statistics Discipline subject, one Computer Science Core Discipline subject and one Computer Science Discipline subject.
At the completion of the Master of Data Science, students will have acquired the knowledge covered by the Foundation, Core and Capstone subjects. They will also have completed selected statistics and computer science specialisation subjects that deepen their knowledge of both statistics and computer science and may have completed additional general or internship subjects.
Changing specialisations
In order to change specialisation, you will need to demonstrate to the course coordinators that you have completed the required Foundation subjects, or have received non credit exemptions for Foundation subjects based on previously completed study. You must also ensure that your course plan meets the requirements of your chosen specialisation.
To change specialisations, you must:
- Demonstrate completion of the required Foundation subjects or their equivalent
- Submit your request to the course coordinators, including;
- Your official University of Melbourne offer letter
- Your transcript or statement of results for all previously completed studies
- A proposed course plan
Who should I contact?
- To move to the Statistical Data Science specialisation contact Statistics Coordinator, A/Prof Karim Seghouane.
- To move to the Computational Data Science specialisation contact the Computer Science Coordinator, Dr Jean Honorio.
- To move to the Computational and Statistical Data Science specialisation contact both coordinators above.
Troubleshooting Foundation subjects
Please note that it is your responsibility to ensure that all required Foundation subjects are completed before enrolling in Core subjects to ensure that all Core subject prerequisites are met.
To enquire about:
- MAST90105 Methods of Mathematical Statistics
- MAST90104 A First Course In Statistical Learning
You should contact the Statistics Coordinator, A/Prof Karim Seghouane.
To enquire about:
- COMP90041 Programming and Software Development
- COMP90038 Algorithms and Complexity
- COMP20008 Elements of Data Processing
- INFO90002 Database Systems & Information Modelling.
You should contact the Computer Science Coordinator, Dr Jean Honorio.
An example
A student admitted to the Computational Data Science specialisation who has been granted 37.5 credit points of non-credit exemption may change to the Statistical Data Science specialisation after completing, in their first year, the remaining Foundation subjects identified as not having been satisfied through previous study, as well as one Computer Science Core Discipline subject.
This is because the student would still have 25 credit points of non-credit exemption available, which can be used to complete one Statistics Core Discipline subject and one Statistics Discipline subject, thereby meeting the requirements of the Statistical Data Science specialisation.