The Master of Data Science is designed to prepare students to work on the forefront of data-driven decision-making and forecasting. Build on your existing undergraduate qualification and/or industry experience as you develop an in-depth understanding of activities and processes related to managing, interpreting, understanding and deriving knowledge from large data sets.
In this course, you’ll learn how to gain meaningful insight from data obtained from business, government, scientific and other sources. Expand your knowledge and understanding of computer science and data analytics, develop skills in state-of-the-art techniques and contemporary tools covering the entire data management lifecycle.
The Master of Data Science is designed for postgraduate students who wish to extend their knowledge of computer science and data analytics in order to be able to gain meaningful insights from data coming from a variety of sources (business, governments, science).
Students will develop skills in state-of-the-art techniques and gain experience in contemporary tools covering a variety of aspects of the entire data management lifecycle, allowing them to work at the forefront of data-driven decision making and forecasting.
This advanced postgraduate course will build on students’ cognate undergraduate qualifications or relevant industry experience by developing an in-depth understanding of the activities related to managing, interpreting, understanding and deriving knowledge from large data sets.
Career opportunities
Graduate will have skills in state-of-the-art techniques and experience in contemporary tools covering a variety of aspects of the entire data management lifecycle, allowing them to work on the forefront of data-driven decision making and forecasting.
Aims and objectives
At the completion of the Master of Data Science course, graduates will be able to:
- demonstrate and apply a coherent understanding of the concepts and practices within the field of Data Science as an effective member of diverse teams in a professional context
- critically analyse various data science scenarios, evaluate the existing knowledge base, and propose and justify effective and/or innovative solutions, including the choice of appropriate technology
- demonstrate personal discipline, scholarship of the field, critical thinking, and judgment by completing substantial projects with industry relevance
- communicate information proficiently to technical and non-technical audiences, including industry practitioners
- apply knowledge of research principles and methods to solve diverse Data Science problems from scenarios relevant to science and/or industry and critically reflect on the appropriateness of the solution
- reflect on, and take responsibility for their own learning, manage their own time and processes effectively by --regularly reviewing personal performance as a means of managing continuing professional development.
