Overview

This topic offers an in-depth exploration of the key concepts, techniques, and tools necessary for data engineering, focusing on preparing data for analytics and decision-making processes. Students will gain hands-on experience in designing and implementing data pipelines and applying advanced data transformation, modelling, and analytics techniques. By leveraging modern data … For more content click the Read More button below.

Topic availabilities

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Tuition pattern

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Aims

This topic aims to:

  • Develop a strong foundation in data engineering principles.
  • Equip students with practical data pipeline design and implementation skills.
  • Foster expertise in data transformation, modelling, and analytics.
  • Instil a deep understanding of data quality, security, and privacy.
  • Introduce modern data platforms and architectural solutions.
  • Enable students to support data-driven decision-making and AI integration.

Assessments

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Current students should refer to FLO for detailed assessment information, including due dates. Assessment information is accurate at the time of publishing.

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Requisites information

Pre-requisites:
Anti-requisites:

Assumed knowledge

Basic Knowledge of Statistics; Sound knowledge of at least one programming/scripting language, e.g., C++/Java/Matlab/R/Python