Data Science and Computing for Engineers

Learning Outcomes

Engineering analysis

Having successfully completed this module you will be able to:

• B2 - Students develop the ability to analyse broadly-defined problems reaching substantiated conclusions using first principles of mathematics, statistics, natural science and engineering principles, assessed through structured and open-ended tasks in Semester 2.
• B3 - Semester 2 brief requires application of appropriate computational and analytical techniques to model complex engineering problem, reflections on the limitations of the methods used.

The Engineer and Society

Having successfully completed this module you will be able to:

• B8 - A lecture on ethics - including data science ethics and guidelines - is given in semester 1, followed up with further resources (reading materials) on Blackboard.
• B10 - A lecture on cybersecurity - including data management - is given in semester 1, followed up with further resources (literature, reading materials) on Blackboard.
• F9 - Semester 2 brief requires evaluating data uncertainty and applying statistical analysis to identify, assess, and mitigate risks associated with the engineering problem.

Science and Mathematics

Having successfully completed this module you will be able to:

• B1 - Semester 2 brief requires application of mathematics, statistics, and engineering principles to broadly defined data-driven problems, using computational tools and methods.

Engineering practice

Having successfully completed this module you will be able to:

• B17 - Semester 2 coursework portfolio requires effective communication with technical and non-technical audiences.

Summative

This is how we’ll formally assess what you have learned in this module.