Computational Thinking and Jupyter Notebooks¶
Engineering analysis is a systematic process that leverages computational thinking paradigms (models) for analyzing and understanding problems in the various fields of engineering. Sucessful application of the process requires familarity with generic problem-solving techniques, understanding of relevant engineering fundamentals that apply to the particular problem, and a working knowledge of computational thinking solution procedures.
It is also helpful to have a computer-based computation environment where stored instructions (a program) can be implemented to solve the problem easily once the problem is defined and set-up. In this course that environment is a Jupyter Notebook using the iPython kernel. Collectively we refer to these jointly as our Jupyter Notebook.
Note
Other kernels can be used, \(\textit{R}\) is probably the other most common kernel in use. Python was selected by the WCOE as the target language for engineering students; iPython is a variant that is mostly compatable with regular Python (by compatable I mean code can be cut-and-pasted into a python file and will usually run with minimal modification; the converse is also true).