Academic

Advising

Course Recommendations

Listed below are some wonderful classes offered at Penn that aren't necessarily part of the standard core Physics curriculum. Our members highly recommend looking into them though!

ASTR 211 - Introduction to Astrophysics I

with Ravi Sheth

"Sheth is a great lecturer and very interested in helping you really learn the material of the class. It is a good introduction to a number (although not all!) of subfields within astronomy if you are looking to figure out more specifically what about astro you want to research. It is interesting and valuable to anyone interested in space!"

ASTR 212 - Introduction to Astrophysics II

with Adam Lidz

"If you are at all interested in cosmology (dark matter, the early universe, structures larger than stars/individual galaxies), you must take Astro 212. The material covered in 212 is not accessible except in a university classroom, so taking the class is really essential if you want to get any deeper into cosmology. The math and concepts are challenging, but topics such as inflation, the CMB, and the power spectrum only get less confusing as you are more exposed to them. Because it is such a niche class, there are not that many resources to help you do well in the class (besides the few provided by the prof), but if you pay attention to lectures and go to office hours as needed, you won’t have any problems. Having taken this class, I feel more able to contribute to the research my lab is doing and can understand much more clearly Astro papers."

CIS 110 - Introduction to Computer Programming

with various professors

"In my experience, most physics in practice requires coding. CIS 110 is a great class to take if you have no computer science background, as it is meant for beginners. You will learn a lot about the basics of computer programming, as well an object-oriented programming in particular. These skills are not only desirable by either potential employers or graduate schools, but will be useful for you when you encounter them in practice. The workload is not intense but you gain a lot from it. Computer science is growing increasingly relevant to Physics, and learning the basics in this class is a great place to start."

Chem 115 - Honors Chemistry I

with Jessica Anna

"Chem 115 is largely about electrons and waves– orbitals, particle in a box, schrodinger's equation, etc. While you definitely have to work in this class, it's still taught to an appropriate level for first years and the material is actually applicable to upper level stem classes. Also, it's really nice to have a smaller STEM class freshman year as opposed to huge lectures."

ESE 625 - Nanorobotics

"Focuses on the principles of nano robotics, but is very physics based"

Phys 260 - Computational Physics

with Robert Johnson

"Coding is hard, but Bob Johnson makes it accessible. Also, this class covers a huge variety of applications and mathematical techniques– there's astrophysics, E+M, thermodynamics, and more. Bob is really willing to help individual students with their code, encourages hands-on learning and small group discussion, and actually seems to care a lot about his students and their wellbeing. "

Phys 280 - Biophysics

with Phil Nelson

"Often considered to be the intro biophysics class, Phys 280 is relevant to so many more fields than just biological applications of physics. As a matter of fact, one of my favourite parts of this class was seeing its overlap with Astro 211, which I was taking at the same time. The course covers a very wide range of subjects, from diffraction to Bayesian statistics to computational analysis, all of which are incredibly practical skills to have in any field of research. More than anything, though, Phil Nelson challenges the way you think in this class, which is what makes it so valuable."

Phys 585 - Theoretical and Computational Neuroscience

with Vijay Balasubramanian

"The high level of this class is intimidating, but it is very doable for undergrads, even as early as sophomore year! The focus of Phys 585 is two-fold: first, you are introduced to the theoretical basis for current neuroscience research and second, you are pushed to explore old and new computational models of systems of neurones Lectures, from the absolutely incredible Vijay Balasubramanian, focus on theory with math and biology that is easy to understand. The class moves fast enough to constantly be keeping students interested. Homeworks are where you get to work with computational models. Some of them can be very, very difficult, but working in teams and starting early enough certainly makes them possible. For this reason, I would strongly recommend only taking this class if you have prior matlab or python coding experience and have taken Phys 280! By the end of the class, you will be so proud of what you have accomplished. Seriously, the feeling of accomplishment is unmatched by any other class I have taken so far at Penn. "