Choose Master of Data Science at LaTrobe
Data scientists are in short supply but in demand by many industries. Rapid technological advances have created large volumes of complex data, and companies are seeking experts who can use this data to their advantage. Companies are competing fiercely for experts who can find ways to manage higher volumes of data and solve increasingly complex challenges.
La Trobe’s Master of Data Science is designed to give graduates a competitive edge through up-to-the-minute theoretical content, real-world practical experiences, and networking opportunities with industry leaders.
La Trobe ranks ‘above world standard’ for mathematical sciences and pure mathematics research and ‘well above world standard’ for statistics research in the 2015 ERA Australian Research Council rankings. You'll learn from academics who are at the forefront of the Big Data field. Students are taught the latest data science tools such as Apache Spark and Hadoop.
Select from one of three majors: bioinformatics, big data and cloud computing, or analytical science, and broaden your knowledge through a range of electives.You'll graduate ready to tackle society’s next generation of challenges using your unique skills in big data computing, analytical modelling and intelligence systems.
Data scientists work across sectors such as business, health, biology, logistics, information technology and more, to interpret big data and identify innovative opportunities.
La Trobe works in an industry with hospitals, large internet companies and the Australian Institute of Sport to solve real-world data problems.
As a graduate, you'll be well positioned for a career in a variety of roles including:
supply chain analyst
This course allows you to work in any sector where data can help solve problems, this may be in fields such as:
The Master of Data Science is a two-year degree which enables students to develop the knowledge and skills to work as data scientists in a wide range of industries including science, business, health, agriculture, sport, transport, or logistics. There is increasingly high demand for an accurate extraction of insightful knowledge from big data collection, and for the ability to make predictions on future trends and performance. The complexity and volume of big data collections (images, documents, social media data, streaming sensor data) drives the need for a unique set of skills in big data computing, analytical modelling and intelligence systems which underpins the Data Science degree.
Specifically, this course has three major specialisation areas:
Big Data and Cloud Computing
Each major includes a set of core advanced subjects from the computer science and mathematics/statistics disciplines and a number of specialised advanced subjects including big data management, computational intelligence for analytics, data exploration and visualisation, cloud systems development, analysis of repeated measures data, meta-analysis, and bioinformatics technologies.
The course requires the completion of 240 credit points over two years of full-time or equivalent part-time study with a minimum of 120 credit points completed at fifth-year level.
Course intended learning outcomes
Course Intended Learning Outcomes (CILOs) are brief statements defining what students are expected to demonstrate they know and can do by the end of a course.
Communicate information and critical analysis in the fields of data science. Critically analyse and solve problems in the fields of data science by using multi-disciplinary approaches. Demonstrate the ability to assess whether the application of computing techniques and mathematical and statistical approaches are appropriate for a particular scientific problem in the fields of data science. Demonstrate a highly developed, integrated understanding and ability to apply complex theoretical concepts that underpin the field of data science.
Big data and cloud computing specialisation
Analytical Science Specialisation
Prerequisites: Australian Bachelor degree (or equivalent) in computer science, information technology, computer engineering, or science with a major in mathematics or statistics. NB: Meeting minimum prerequisites does not guarantee an offer of a place. Entry into all La Trobe courses is based on competitive selection and there may be limited places available.
Additional information: This course requires prior knowledge in cognate areas of either Computer Science, IT, and/or Mathematics and Statistics. The course starts with a semester of core fundamental subjects designed to address knowledge gaps in the required cognate skills. E.g. students who have completed a Computer Science degree will need to choose fundamental subjects in Statistics and vice versa.