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Curtin University

  • 28% international / 72% domestic

Data Analytics and Visualisation Specialisation

  • Non-Award

In this Master of Information Systems and Technology specialisation, you'll develop the skills required for senior-level roles in data analytics and visualisation.

Key details

Degree Type
Non-Award

About this course

Outline Outline

In this Master of Information Systems and Technology specialisation, you'll develop the skills required for senior-level roles in data analytics and visualisation.

You'll learn to understand and apply broad concepts in data mining, business intelligence and data interpretation to make informed business decisions.

As a consumer and producer of data, you'll learn about data management and security practices, and develop an understanding of the legal and ethical issues related to collecting and using data.

Please refer to the handbook for additional course overview information.

What you'll learn
  • apply data analytics techniques to large and complex datasets, using statistical, machine learning, and data mining methods to extract insights, identify patterns, and make data-driven decisions, GC1, GC3.
  • create effective data visualizations and dashboards, by selecting appropriate visual encoding techniques, designing clear and concise interfaces, and presenting insights in a way that is engaging and understandable to different stakeholders, GC2, GC3.
  • develop and implement data analytics solutions, including data preparation, integration, and transformation, and use cloud-based tools and technologies to support scalable and efficient data processing and analysis, GC1, GC4, GC5, GC6.
  • evaluate the ethical and legal implications of data analytics, by understanding and applying principles of data governance, privacy, and security, and by ensuring that data analytics and visualization projects adhere to relevant regulations and standards

What you will learn

  • apply data analytics techniques to large and complex datasets, using statistical, machine learning, and data mining methods to extract insights, identify patterns, and make data-driven decisions, GC1, GC3.
  • create effective data visualizations and dashboards, by selecting appropriate visual encoding techniques, designing clear and concise interfaces, and presenting insights in a way that is engaging and understandable to different stakeholders, GC2, GC3.
  • develop and implement data analytics solutions, including data preparation, integration, and transformation, and use cloud-based tools and technologies to support scalable and efficient data processing and analysis, GC1, GC4, GC5, GC6.
  • evaluate the ethical and legal implications of data analytics, by understanding and applying principles of data governance, privacy, and security, and by ensuring that data analytics and visualization projects adhere to relevant regulations and standards