An introduction to Soft OR and the methods for working with strategic and complex problem situations and structuring qualitative data.
A practical introduction to the most used methodologies in OR, linear programming and optimisation.
Explore the operational research methods and models available for supporting strategy.
A practical course using multivariate statistical techniques to gain greater insights from your analysis.
This practical course will help you to improve project performance, ensure outcomes are met and enable resources to be used efficiently, using Soft Systems Methodology (SSM).
This course offers a set of frameworks and methods based on behavioural science to support Operational Research (OR) Practice.
Gain an understanding of the ideas and concepts of efficiency assessment of organisations and how Data Envelopment Analysis (DEA) models can be formulated and applied using Excel Solver.
Gain the theoretical and practical understanding on how to process and model time series data in your analytical and forecasting workflows using R programming language.
An introductory course to equip you with a tool bag of core quantitative forecasting techniques that are adaptable to almost any organisational setting.
The language of data visualisation and how to apply it to your everyday methods and analysis.
Develop a practical understanding of System Dynamics qualitative and quantitative methods.
Understand how to present their facts in the most compelling manner. Familiarity with Key Principles.
Offers a set of frameworks and methods based on behavioural science to support Operational Research (OR) Practice. The course can be useful for developing behavioural OR models, understanding behavioural issues with the implementation of OR models.
Practical introduction to simulation modelling, allowing you to understand the benefits of simulation and when to use it.
Gain an understanding of the wide spectrum of skills used in Operational Research, including: problem structuring; data collection; analytics; modelling; and simulation. Learn and understand a typical problem cycle.
A follow on course the Foundation course in forecasting and for those who wish to develop their toolbox further with Autoregressive Integrated Moving Average (ARIMA).