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Master of Data Science (MC-DATASC) // Attributes, outcomes and skills
You’re currently viewing the 2020 version of this course
About this course
Coordinator
Howard Bondell
Coordinator
Trevor Cohn
Contact
Currently enrolled students:
- General information: https://ask.unimelb.edu.au
- Contact Stop 1
Future students:
- Further information: http://science.unimelb.edu.au/
Intended learning outcomes
On completion of the course, students should be able to:
- Demonstrate a detailed technical understanding of the key advanced tools and methods used in data science;
- Demonstrate expertise in machine learning methods and strategies for advanced data mining, expertise in database systems, and expertise in computational statistics.
- Integrate and apply this expertise to produce solutions for real-world problems using public and private data sources.
- Demonstrate a sophisticated awareness of ethical implications relevant to the use of data, and particularly “big data”;
- Demonstrate skills in the evaluation and synthesis of information from a range of sources and the ability to apply these skills to understand the international peer-reviewed scientific literature and primary research in data science and disciplines relevant to data science;
- Have the ability to adapt to a rapidly evolving field.
Generic skills
Graduates will:
- Have the ability to demonstrate advanced independent critical enquiry, analysis and reflection
- Have a strong sense of intellectual integrity and the ethics of scholarship
- Have in-depth knowledge of their specialist area
- Reach a high level of achievement in writing, research or project activities, problem-solving and communication
- Be critical and creative thinkers, with an aptitude for continued self-directed learning
- Be able to examine critically, synthesise and evaluate knowledge across a broad range of disciplines
- Have a set of flexible and transferable skills for different types of employment; and
- Be able to initiate and implement constructive change in their communities, including professions and workplaces
Graduate attributes
Graduates have a sound knowledge of modern statistical methodology and computing that will equip them for a career in data science and enable their careers to develop as data science evolves.
Graduates will:
- have the ability to demonstrate advanced independent critical enquiry, analysis and reflection;
- have a strong sense of intellectual integrity and the ethics of scholarship;
- have in-depth knowledge of modern statistical methodology and computing
- reach a high level of achievement in writing, research or project activities, problem-solving and communication;
- be critical and creative thinkers, with an aptitude for continued self-directed learning;
- be able to examine critically, synthesise and evaluate knowledge across a broad range of disciplines;
- have a set of flexible and transferable skills for different types of employment; and
- be able to initiate and implement constructive change in their communities, including professions and workplaces
Last updated: 18 December 2020