Data Science Curriculum

The Master of Data Science (MDS) provides students from a quantitative background with a pathway to specialise in intelligent data-driven systems. Students will develop the analytical and technical skills to use data science to guide decision-making; exploring data mining, machine learning and data visualisation.

Sydney Data Science Online offers a 24-credit point Graduate Certificate, a 48-credit point Graduate Diploma, and a 72-credit point Masters Degree. Students who complete either the Graduate Certificate or 24 credits of the Graduate Diploma (including 12 credit points of Data Science Core Credit Points and 12 credit points of Data Science specialist elective Credit Points) with a minimum 65% credit average can apply to complete the full Masters Degree even if they do not meet the cognate degree requirements.

Data Science Coursework

Data Science Core	Grad Cert: 12 Credit Points Required Grad Diploma: 12 Credit Points Required Masters: 18 Credit Points Required	Visual Analytics Principles of Data Science Computational Statistical Methods
Professional Core	Grad Diploma: 6 Credit Points Required Masters: 12 Credit Points Required	Professional Practice in IT Understanding IT Innovations
Specialisation Credit Points	Grad Cert: Choose 12 Credit Points Grad Diploma: Choose 24 – 30 Credit Points Masters: Choose 24 – 30 Credit Points (Will result in completion of either Machine Learning or Data Engineering Specialisation)	Machine Learning and Data Mining (ML) Advanced Machine Learning (ML) Deep Learning (ML) Advanced Data Models (DE) Cloud Computing (DE) Data Engineering (DE)
Elective	Grad Diploma: Choose 0 – 6 Credit Points Masters: Choose 0 – 6 Credit Points	Parallel and Distributed Computing
Project	Masters: 12 Credit Points Required	Capstone Project (x2)

Masters Specialisations

All students will complete one of the following specialisations through their selection of elective courses:

Machine Learning: The Machine Learning specialisation will help you build the skills required to make computers learn from data without being explicitly programmed. Machine learning is one of the most popular approaches to achieve Artificial Intelligence. Students will be exposed to various types of data from the real world, learn concepts and technologies to recognise, abstract and solve the machine learning problems, and push the boundary of machine learning for social good.

Data Engineering: The Data Engineering specialisation will explore how data can be stored, accessed and processed, at large scale. It covers a variety of different computational environments, including cloud-hosted ones. Data science and machine learning is opening up opportunities everywhere to improve decisions using large amounts of data. The Data Engineering specialisation will prepare you for the work of data science teams and utilising effective hardware and software infrastructure.