Date : 12-13 March 2020 (Thursday – Friday)
Time : 9:00am – 5:00pm
Venue : National University of Singapore
This course introduces strategies for data collection and analysis aimed at efficient empirical studies of new, unknown, or complex systems commonly encountered in civilian as well as military applications. The objective is to establish optimal operational conditions and parameters of such systems without costly and lengthy trials and modifications. Familiarity with these strategies is essential for meeting requirements such as time-to-market, time-to-deployment, and excellence in operational cost-effectiveness.
This course aims at imparting to the participants the essence of data-based analytical techniques for understanding and management of hardware or man-machine systems.
At the end of this course, participants will understand the role and use of data-based analytical techniques not available in common diploma and degree courses.
Participants are encouraged to bring their cases for discussion, illustration, and possible solution.
Who Should Attend
~ Managers and personnel with responsibilities for studying or operating hardware or man-machine systems
~ those seeking effective techniques of problem solving and decision-making.
The discussions will be practical, generic and not confined to any particular industry or business sector.
“O” level mathematics and familiarity with Windows operating system.
~ Performance improvement and optimisation
~ Approach to new, unknown, or complex systems
~ Empirical studies and data analytics
~ Theoretical vs real-world performance
~ Limitations of conventional methods
~ Purposes, types and uses of models
~ Design and implementation of empirical studies
~ Handling of the uncontrollable or unpredictable
~ Efficient characterisation of multiple parameters
Analysis and Optimization
~ Multiple-objective systems
~ Software selection and demonstration
~ Further approaches and techniques
For more information and registration, do send an email to email@example.com (Ms Sim Kah Eng, Queenie)
Please refer here for more information.