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Curtin University

  • 28% international / 72% domestic

Data Science Major (M PredAnylt)

  • Non-Award

The Data Science Major consolidates data science and predictive analytics skills through core machine learning and project units along with a range of optional units.

Key details

Degree Type
Non-Award
Study Mode
Online

About this course

Outline Outline

The Data Science Major consolidates data science and predictive analytics skills through core machine learning and project units along with a range of optional units. Available options extend knowledge in artificial intelligence, statistics, networking and internet of things, cloud computing, security and/or industrial automation. Graduates may find employment in data analytics across a wide range of fields, particularly as an enhancement to their current academic qualifications and experience.

What you'll learn
  • Apply advanced algorithms and statistical theory in the exploration, analysis and presentation of data.
  • Provide innovative and creative solutions utilising data science knowledge and analytical methods.
  • Communicate the implementation and outcomes of data collection, processing and presentation to both expert and non-technical audiences.
  • Apply and devise new approaches to data science - potentially addressing global problems through analysis and simulation; endeavour to comply with standards and guidelines relevant to data science and to the application domain.
  • Develop solutions and analyses that respect confidentiality, ethics, sustainability and maintain social responsibility.
  • Demonstrate initiative and leadership when working independently and collaboratively using problem solving and decision-making skills.

Study locations

Online

What you will learn

  • Apply advanced algorithms and statistical theory in the exploration, analysis and presentation of data.
  • Provide innovative and creative solutions utilising data science knowledge and analytical methods.
  • Communicate the implementation and outcomes of data collection, processing and presentation to both expert and non-technical audiences.
  • Apply and devise new approaches to data science - potentially addressing global problems through analysis and simulation; endeavour to comply with standards and guidelines relevant to data science and to the application domain.
  • Develop solutions and analyses that respect confidentiality, ethics, sustainability and maintain social responsibility.
  • Demonstrate initiative and leadership when working independently and collaboratively using problem solving and decision-making skills.