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. The evaluation for this module involves a combination of individual project assignments and a final practical class test.
NOTE: COMP41680 requires a reasonable level of prior programming experience (but not necessarily in Python).
NOTE: COMP41680 requires a reasonable level of prior programming experience (but not necessarily in Python).
About this Module
Student Effort Hours:
| Student Effort Type | Hours |
|---|---|
Not yet recorded. |
|
Requirements, Exclusions and Recommendations
Not applicable to this module.
Module Requisites and Incompatibles
Not applicable to this module.
Assessment Strategy
| Description | Timing | Component Scale | % of Final Grade | ||
|---|---|---|---|---|---|
Not yet recorded. |
|||||
Carry forward of passed components
Not yet recorded
Not yet recorded
| Terminal Exam |
|---|
Not yet recorded |
Not yet recorded
| Name | Role |
|---|---|
| Dr Timilehin Aderinola | Lecturer / Co-Lecturer |
| Professor Pádraig Cunningham | Lecturer / Co-Lecturer |