List of Courses Taken

A personal record of what I’ve learned throughout my 4+ years of post-secondary education.

Traditional Courses

Amherst College

Mathematics

  • MATH 271 Linear Algebra
  • MATH 350 Groups, Rings and Fields
  • MATH 355 Introduction to Analysis
  • MATH 385 Mathematical Logic
  • MATH 415 Topics in Mathematics: Computational Algebraic Geometry
  • MATH 421 Complex Variables (UMass Amherst)

Music

  • MUSI 113 Jazz Theory & Improvisation I
  • MUSI 241 Harmony & Counterpoint I
  • MUSI 242 Form in Tonal Music
  • MUSI 265 Electroacoustic Music
  • MUSI 269 Composition I
  • MUSI 310 Performance and Analysis II
  • MUSI 371/2 Composition Seminar I/II
  • MUSI 422 Music and Revolution: Mahler and Shostakovich
  • MUSI 444 Twentieth Century Analysis
  • MUSI 498 Senior Honors

Physics

  • PHYS 123 Newtonian Synthesis
  • PHYS 124 Maxwellian Synthesis
  • PHYS 225 Modern Physics
  • PHYS 226 Intermediate Laboratory
  • PHYS 227 Methods of Theoretical Physics
  • PHYS 230 Statistical Mechanics & Thermodynamics
  • PHYS 343 Dynamics
  • PHYS 347 Electromagnetic Theory I
  • PHYS 348 Quantum Mechanics I
  • PHYS 498 Senior Honors

other

  • COSC 111 Introduction to Computer Science I
  • ENGL 338 Shakespeare
  • FYSE 108 First Year Seminar: Evolution & Intellectual Revolution
  • GREE 111 Introduction to Greek Language
  • GREE 212 Plato’s Apology
  • PHIL 111 Introduction to Philosophy
  • PHIL 335 Theory of Knowledge

Harvard University

  • Physics 232 Advanced Electromagnetism
  • Physics 251a Advanced Quantum Mechanics I
  • Physics 251b Advanced Quantum Mechanics II
  • Physics 262 Statistical Physics
  • Physics 253a Quantum Field Theory I
  • Physics 285a Atomic, Molecular and Optical Physics
  • Physics 210 General Relativity
  • Physics 201 Data Analysis for Physicists

Online Courses

Screenshot of my Coursera accomplishments page can be found here.

Data science and machine learning

  • Machine Learning (Stanford University)
  • The Data Scientist’s Toolbox (Johns Hopkins University)
  • R Programming (Johns Hopkins University)
  • Getting and Cleaning Data (Johns Hopkins University)
  • Exploratory Data Analysis (Johns Hopkins University)
  • Reproducible Research (Johns Hopkins University)
  • Statistical Inference (Johns Hopkins University)
  • Practical Machine Learning (Johns Hopkins University)
  • Developing Data Products (Johns Hopkins University)

Bioinformatics

  • Finding Hidden Messages in DNA (Bioinformatics I) (UC San Diego)

Humanities

  • The Ancient Greeks (Wesleyan University)
  • Philosophy and the Sciences (University of Edinburgh)
  • Big History: Connecting Knowledge (Macquarie University)