Who should attend
This class is designed for business analysts, scientists, and engineers who have not completed a Ph.D.
About the course
This class builds on the core ideas in the Principles of Problem Solving class and introduces a rigorous problem-solving framework built around the notion of the modern problem solver — and encourages you to become one! The modern problem solver is a person who can build informative models (both qualitative and quantitative) of the problem at hand and use these models to gain insight to support decision making and further learning. This person also is someone who augments his or her domain knowledge with mathematical, statistical, and programming skills to create computational models that drive insight. Are you interested in honing your skills on how to create and apply simple models to aid in decision making? If so, you will find this class enormously beneficial.
What You Will Learn
- The modern problem solver and the five elements of effective thinking
- Statistical thinking and how it is related to problem solving
- A formal introduction to systems engineering conceptual design and how it is a sound methodology for model-based problem solving
- An overview of the seven management and planning tools for building rigorous, qualitative models
- Tools and techniques learned in the class through two case studies
How You Will Benefit
- Improve how you assess and tackle complex, ill-defined problems.
- Gain a better understanding on how to improve your ability to learn new topics and explore wicked problems.
- Learn how to build simple qualitative and quantitative models of complex problems to gain insight.
- Apply tools and methods developed in the systems engineering field to add additional structure to model building and learning.
- Review of wicked problems and opportunity driven problem solving
- Introduction to the modern problem solver
ELEMENTS OF EFFECTIVE THINKING
Introduction to the five elements of effective thinking and learning * Reintroduction to the scientific method * Overview of statistical thinking and how it is related to problem solving
MODEL BASED PROBLEM SOLVING
- Introduction to systems engineering conceptual design and how it is a sound methodology for model-based problem solving
- Formal introduction to model-based problem solving
- Discussion on the differences between expert modelers and novice modelers
- Overview of the seven management and planning tools for building rigorous, qualitative models
MODELING FOR INSIGHT
- Introduction and application of the Modeling for Insight formal modeling process for creating quantitative models
- Introduction and application of Python and Jupyter Notebook as a means to lower the barrier to model building for those students that aren't “programming experts”
MODELING CASE STUDY
Two case studies to reinforce the tools and techniques learned in the class
Dr. Jack Zentner is a Senior Research Engineer at the Electronic Systems Laboratory (ELSYS) in the Georgia Tech Research Institute (GTRI). His primary area of research is in the development of and application of systems engineering tools and methods to the design of large scale, complex systems. ...
Because of COVID-19, many providers are cancelling or postponing in-person programs or providing online participation options.
We are happy to help you find a suitable online alternative.