Module overview
Linked modules
Prerequisites: MANG1019 or MANG1047
Aims and Objectives
Learning Outcomes
Transferable and Generic Skills
Having successfully completed this module you will be able to:
- communicate effectively.
- plan and control effectively for successful completion of a personal workload;
- produce an integrated written report at an appropriate intellectual and practical level;
Subject Specific Intellectual and Research Skills
Having successfully completed this module you will be able to:
- interpret the output of statistical techniques used for the main data analytics applications.
- explain and evaluate concepts and tools needed to evaluate, analyse, and interpret large volume of data in different industries;
- plan the resources needed to evaluate and analyse data, critically apply findings, and disseminate the outcomes;
Knowledge and Understanding
Having successfully completed this module, you will be able to demonstrate knowledge and understanding of:
- the use of advanced analytics methods on large volume of data to derive actionable insights in different industries.
Syllabus
Learning and Teaching
Teaching and learning methods
Type | Hours |
---|---|
Teaching | 34 |
Independent Study | 116 |
Total study time | 150 |
Resources & Reading list
Textbooks
VanderPlas, J. (2022). Python Data Science Handbook.. Sebastopol, CA: O’Reilly Media.
Provost, F. and Fawcett, T. (2013). Data science for business. O’Reilly.
Han, J., Pei, J. and Tong, H. (2024). Data Mining: Concepts and Techniques. Morgan Kaufmann.
Baig, M.R., Govindan, G. and Shrimali, V.R. (2021). Data science for marketing analytics: a practical guide to forming a killer marketing strategy through data analysis with Python.. Birmingham, UK: Packt Publishing.
Delen, D (2021). Predictive Analytics: Data Mining, Machine Learning and Data Science for Practitioners.. Old Tappan, New Jersey: Pearson Education.
Assessment
Formative
This is how we’ll give you feedback as you are learning. It is not a formal test or exam.
Class participation
- Assessment Type: Formative
- Feedback: There will be exercises and computer laboratories/class sessions for this module. The lecturer will provide verbal feedback during all sessions as well as during office hours.
- Final Assessment: No
- Group Work: No
Summative
This is how we’ll formally assess what you have learned in this module.
Method | Percentage contribution |
---|---|
Project | 100% |
Referral
This is how we’ll assess you if you don’t meet the criteria to pass this module.
Method | Percentage contribution |
---|---|
Project | 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 |
---|---|
Project | 100% |
Repeat Information
Repeat type: Internal & External