## jakehofman.com## teaching |

i co-taught modeling social data (apam e4990) in columbia's applied mathematics department in the spring of 2015.

i co-taught computational social science (apam e4990) in columbia's applied mathematics department in the spring of 2013.

i taught data-driven modeling (apam e4990) in columbia's applied mathematics department in the spring of 2012, a course on data mining and applied machine learning. see the current course site and related code for more information.

i originally designed and taught this class in the fall of 2009.

"simple math for a complex world: random walks in biology and finance": see slides, notes, and movies; see matlab code below for diffusion and random walk demos

i gave a (rather impromptu) tutorial on machine learning at the 2007 boulder summer school for condensed matter and materials physics. the slides and associated demos are availble for download at the school's google group.

i'm lucky enough to have taught a biological physics course for
columbia's saturday morning
science honors program
for high school students. more material to come in the future,
but here are a few things:

some questions given out
on the first day of class

matlab code for a 1-d diffusion demo

matlab code for a 1-d random walk demo

homework solution, derivation of the
gaussian approximation to the binomial

after surviving columbia's qualifying exam i decided to
organize a prep course for first year grad students
in columbia's physics phd program. the the result was a
(hopefully useful) set of problems that were
discussed by each week.

here's the old version of the quals prep site
that has some study guides and references listed. also, here are some
(mostly stolen) example problems for the
electricity and magnetism,
modern physics,
mechanics, and
general physics
sections of the exam.

note: columbia's quals are undergrad level.