Coursework / Training
UC San Diego’s undergraduate bioinformatics program covered mathematics, software development and biology in ways that have remained relevant to my work. After graduating, I pursued further upskilling in statistics, machine learning, neuroscience and psychology to build upon that training and gain greater familiarity with subjects relevant to my interests. The coursework below captures much of my structured learning, but I’ve also learned through research articles, blogs, podcasts, conversations with chatbots and my own experience in therapy.
Statistics:
School Coursework: Statistics for Psychology, Probability and Statistics for Bioinformatics, Calculus 1-3, Discrete Math, Linear Algebra.
Additional Coursework: Following graduation, I rewatched all lectures from my Statistics for Psychology course, redid the assignments and reproduced its SPSS analyses in R (see assignments and R code). I also completed Publication Academy’s statistics course and DataCamp’s 52-hour Statistician in R career track (see certificate).
Machine Learning:
School Coursework: Data Structures, Algorithms, Bioinformatics Algorithms, Advanced Bioinformatics Lab and Biological Databases (see overview).
Additional Coursework: I worked through the public lectures and labs from MIT’s Introduction to Deep Learning bootcamp, completed Andrew Ng’s Machine Learning Specialization and DataCamp’s Deep Learning with PyTorch track (see certificate). I also completed DataCamp courses on scikit-learn and XGBoost.
Psychology and Research Methods:
School Coursework: Research Methods, Clinical Psychology, Social Psychology, Cognitive Psychology, Science of Parenting, AP Psychology.
Additional Coursework: Publication Academy’s Research Methods course. I also worked through Eiko Fried’s network analysis workshop.
Neuroscience/Natural Sciences:
School Coursework: Drugs and Behavior, Molecular Biology, Genetics, Structural Biochemistry, Physics 1-3, Chemistry 1-3, Organic Chemistry, AP Biology.
Additional Coursework: HarvardX’s Fundamentals of Neuroscience (Parts 1–3; approximately 72 hours), Human Behavioral Biology, Fundamental Neuroscience for Neuroimaging, Neurohacking in R (structural MRI data analysis).