Modeling & Simulation of the Physical World is a python based first-year Olin course in which I learned about how to abstract and model physical systems. For this course I completed 7 worksheets, 3 projects, and 2 mini-projects that are guided investigations into Orbital Mechanics and modelling the muliplication of HIV cells using the SEIR model.

My projects:

• Lunch Time in the Olin dining hall
• How much can global sea level rise be mitigated by CO2 emission reduction?
• Creating a glider flight simulation

• Create models of different kinds of systems (e.g., transportation systems, thermal systems, mechanical systems)
• Use multiple kinds of appropriate abstractions (e.g., free-body & stock-and-flow diagrams, differential equations)
• Validate the predictions of models using different approaches (e.g., estimation, physical laws, analytical solutions)
• Use your models to do useful work (e.g., make predictions, explain behavior, evaluate design decisions)
• Use Python to implement models, run simulations, work with data, and generate visualizations
• Communicate technical and quantitative information effectively in several modes (e.g., written, spoken, graphical)
• Work effectively with a variety of teammates and in a variety of roles (e.g., “driver/navigator” in pair programming)
• Be a critical consumer (e.g., assess models encountered, evaluate whether appropriate/useful for given purpose)
• Understand the opportunities and responsibilities involved in creating and using models

"All models are wrong, but some are useful."
      ~ attributed to George Box

"Everything should be as simple as possible, but not simpler."
      ~ attributed to Albert Einstein

The textbook for this course is Modeling and Simulation in Python by Allen B. Downey.