Module overview
This module aims to give students a grounding in the use of statistical software for data manipulation and analysis in Python.
Aims and Objectives
Learning Outcomes
Learning Outcomes
Having successfully completed this module you will be able to:
- Write functions in Python with error handling
- Write and analyse basic programs in Python using built-in functions
- Understand how Python modules enhance program functionality and streamline data operations
- Understand data structures used in Python to store and process data effectively
Syllabus
Introduction to Python
Functions and error handling
Python data structures and Python modules
Learning and Teaching
Teaching and learning methods
Teaching will be through a combination of lectures and computer labs, as well as independent study.
| Type | Hours |
|---|---|
| Independent Study | 60 |
| Teaching | 15 |
| Total study time | 75 |
Assessment
Summative
This is how we’ll formally assess what you have learned in this module.
| Method | Percentage contribution |
|---|---|
| Exam | 100% |
Referral
This is how we’ll assess you if you don’t meet the criteria to pass this module.
| Method | Percentage contribution |
|---|---|
| Exam | 100% |
Repeat
An internal repeat is where you take all of your modules again, including any you passed. An external repeat is where you only re-take the modules you failed.
| Method | Percentage contribution |
|---|---|
| Exam | 100% |