Well, I'm an engineer by day. Although most of my work revolves around modeling, we generally do pretty basic stuff. An "Advanced" model would be a monte carlo simulation validated using R2 tests.
Currently, in my field, there is a lot of research using Logistic and bayesian analysis.
My question is, which courses would you recommend someone to take from MIT's open course site or any other sites, for someone who learns best by video/audio first, and reading second?
What i'd like to learn are the following:
- Be able to understand the models and when to employ them
- able to take in field data (which is generated once and cannot be regenerated) and design and perform experiments
- Able to understand the results, look at them, and figure out if something is off, "show stopper" or "outliers", or if everything is fine and dandy
- Be able to validate and calibrate the model, to actual "As-built" results
- Be able to forecast the results using appropriate sensitivity analysis
- be able to forecast / "plug" missing data
- be able to write journal papers related to my field
my field in a nutshell is: transportation demand modeling for passenger vehicles, using either the generic four step model, or socio economic activity/tour based models such as PECAS or urbansim