During Winter Quarter 2018, I enrolled in a BE188 course taught by Professor Aaron Meyers. We analyzed several bioengineering publications and re-implemented the machine learning algorithms that the authors used. This class was the most impactful class I took at UCLA and encouraged me to look into a career related to data science.

Topics:

You can find the Github repositories for the class here:

Course Description:

Manipulating biological systems requires techniques to interpret complex measurements. Project-based study introduces techniques for inferring biological meaning from experimental measurements using computational and analytical techniques. Objectives including giving students working knowledge of techniques for rigorously analysis of complex data sources; illustration of frontier and open challenges in computational systems biology and bioengineering; and ensuring familiarity with necessary tools to effectively apply computation as part of individual or group research effort. Introduction of foundational applied machine learning and statistics techniques. Laboratory session involves hands-on implementations from recent literature. Includes project-based work using recent literature-derived applications. Includes midterm exam, and final design project involving novel analysis of data derived from literature using course techniques.