Not recorded
The key objectives of this module are
1) to provide students with an initial crash course in Python programming;
2) to familiarise students with a range of key topics in the emerging field of Data Science through the medium of Python.
Students will start by exploring methods for collecting, storing, filtering, and analysing datasets. From there, the module will introduce core concepts from numerical computing, statistics, and machine learning, and demonstrate how these can be applied in practice using popular open source packages and tools. Additional topics that will be covered include data visualisation and working with textual data. This module has a strong practical programming focus and students will be expected to complete two detailed coursework assignments, each involving implementing a Python solution to a data analytics task. COMP47670 requires a reasonable level of mathematical ability, and students should have prior programming experience (but not necessarily in Python).
This is a Mixed Delivery module with online lectures and face to face practicals/tutorials.
1) to provide students with an initial crash course in Python programming;
2) to familiarise students with a range of key topics in the emerging field of Data Science through the medium of Python.
Students will start by exploring methods for collecting, storing, filtering, and analysing datasets. From there, the module will introduce core concepts from numerical computing, statistics, and machine learning, and demonstrate how these can be applied in practice using popular open source packages and tools. Additional topics that will be covered include data visualisation and working with textual data. This module has a strong practical programming focus and students will be expected to complete two detailed coursework assignments, each involving implementing a Python solution to a data analytics task. COMP47670 requires a reasonable level of mathematical ability, and students should have prior programming experience (but not necessarily in Python).
This is a Mixed Delivery module with online lectures and face to face practicals/tutorials.
About this Module
Student Effort Hours:
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Requirements, Exclusions and Recommendations
Not applicable to this module.
Module Requisites and Incompatibles
Not applicable to this module.
Assessment Strategy
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Carry forward of passed components
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| Remediation Type | Remediation Timing |
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