Description
Generating useable data for decision making is a task that needs an awareness of many factors. To be able to do this you need to firstly understand the question being asked and then the data that you possess. Do you have all the data you need? If not, how will you find it? How will you clean it? How will you process it and present it in a way that is beneficial to the decision maker? All these technical questions will be answered in this module.
Aims
The aim of this module is to provide the student with the knowledge and skills required to generate insights from data for decision-making. The module involves Python programming, however previous programming knowledge is not required, as an introductory overview is provided.
Learning Outcomes
By the end of this module the student should be able to:
- Apply suitable pre-processing and analysis techniques to a dataset.
- Develop and evaluate statistical and machine learning models to develop insights about a business problem.
- Effectively communicate complex insights for use in decision-making.
Indicative Content
1 Asking the right questions
Before starting to work with data, a clear understanding of the business questions to be answered with data is needed.
2 Types of data and their sources
Understand the different types of data one might deal with in an organisation, and where these might be obtained from ethically
3 Basics of Python programming
Introduction to programming in Python
4 Data handling and pre-processing
Using appropriate techniques to handle and pre-process raw data into a usable form, using Python
5 Exploratory data analysis
Conduct exploratory and descriptive analysis to understand key issues in the data, using Python
6 Fundamental concepts in statistical modelling and machine learning
Fundamentals of statistical modelling and machine learning, using Python
7 Data visualisation and communication
Employ suitable data visualisation technique to effectively communicate findings, using Python
| Teaching and Learning Method | Hours |
|---|---|
| Lecture | 0 |
| Tutorial/Seminar | 0 |
| Supervised Practical Activity | 0 |
| Unsupervised Practical Activity | 30 |
| Assessment | 40 |
| Independent | 80 |
Guidance Notes
SCQF Level - The Scottish Credit and Qualifications Framework provides an indication of the complexity of award qualifications and associated learning and operates on an ascending numeric scale from Levels 1-12 with SCQF Level 10 equating to a Scottish undergraduate Honours degree.
Credit Value – The total value of SCQF credits for the module. 20 credits are the equivalent of 10 ECTS credits. A full-time student should normally register for 60 SCQF credits per semester.
Disclaimer
We make every effort to ensure that the information on our website is accurate but it is possible that some changes may occur prior to the academic year of entry. The modules listed in this catalogue are offered subject to availability during academic year 2025/6, and may be subject to change for future years.