Prescriptive Analytics for Decision Making - BUSN9970

Looking for a different module?

Module delivery information

Location Term Level1 Credits (ECTS)2 Current Convenor3 2024 to 2025
Canterbury
Autumn Term 7 15 (7.5) Vedat Bayram checkmark-circle

Overview

Set yourself apart and get ahead in your career when you become an expert in prescriptive analytics and how it can be used for decision-making for businesses. You'll cultivate a deep understanding of quantitative models for decision-making and solution techniques, applying industry-standard software such as Excel/OPL-CPLEX to address real world issues and provide solutions. Gain skills aligned with the UN Sustainable Development Goals, empowering you to deliver actionable recommendations that positively impact businesses, society and the environment. You'll finish this module with the ability to strategically apply diverse optimisation techniques in a real world context. Empowered by this knowledge, you'll be poised to make informed decisions, drive positive change, and advance your career with a unique blend of analytical skills and a commitment to ethical, sustainable and diverse decision-making.

Details

Contact hours

Total contact hours: 42
Private study hours: 108
Total study hours: 150

Method of assessment

Main assessment methods:
Individual Written Assessment on Mathematical Modelling and Computation (2000 words): 30%.
Exam (2 hours): 70%

Reassessment methods
Reassessment Instrument: 100% Exam

Indicative reading

See the library reading list for this module (Canterbury)

Learning outcomes

The intended subject specific learning outcomes.
On successfully completing the module students will be able to:
- Demonstrate a comprehensive understanding of quantitative models for decision making.
- Demonstrate conceptual understanding of how complex real-world systems can be represented in mathematical form.
- Exhibit a systematic knowledge of some classic business, management, and industry problems, formulate them mathematically, and solve them.
- Demonstrate an ability to deal with various real-world complexities and incorporate these into the modelling framework in order to prescribe actionable recommendations.
- Implement such models using industry-standard software and perform analyses to support business planning and management.

The intended generic learning outcomes.
On successfully completing the module students will be able to:
- Independently apply their model building, problem-solving and numerical skills to solve complex business/management/industry problems.
- Demonstrate an ability to select the most appropriate technique for a particular business/management/industrial problem.
- Independently analyse the outcome of a model and present their findings in a clear yet rigorous manner.

Notes

  1. Credit level 7. Undergraduate or postgraduate masters level module.
  2. ECTS credits are recognised throughout the EU and allow you to transfer credit easily from one university to another.
  3. The named convenor is the convenor for the current academic session.
Back to top

University of Kent makes every effort to ensure that module information is accurate for the relevant academic session and to provide educational services as described. However, courses, services and other matters may be subject to change. Please read our full disclaimer.