Getting Started#
This course is designed to build expertise in two key areas:
Monte Carlo
Technical Writing
Engineering practice takes many forms, but at its core engineers are defined by how they innovate using quantifiable methods.
Monte Carlo is a skillset that uses random numbers to create computational experiments. Monte Carlo experiments can quantify and predict a number of outcomes e.g. deterministic parameters such as areas and columes, probability of failure, propagation of error.
Technical writing is a crucial skill to communicate innovations, predictions, and results. Technical communication is the delivery of technical information to readers in a manner that is adapted to their needs, level of understanding, and background. The ability to “translate” technical information to nonspecialists is a key skill to any technical communicator.
Our first goal in the course is to practice technical reading and writing to develop personal learning outcomes.
1. Criticize and edit generative AI outcomes - Identify and revise passive voice constructions in technical writing - Improve technical documents for conciseness by eliminating unnecessary words and redundancies - Proof read work to identify and improve technical communications - Quantify generalizations made by generative AI claims - Quantify changes in a doument to attribute authorship and intellectual property
2. Discuss Uncertainty in Design: - Perform statistical analysis of simulation data to extract meaningful insights - Present statistical findings clearly and concisely - Distinguish between qualitative (social) and quantitative (engineering) uncertainty in technical documents - Illustrate the importance of social uncertainty in engineering design
5. Research Engineering Designs and Processes - Find, review, and cite reliable sources of information (textbooks, articles, journals, news sources) - Contextualize technical and social information to validate a design or process - Compose a unique case study in engineering decisions using data from models and sources