Learning
I have always valued self-directed learning, especially in areas that support my work in computational biology. Online courses have been an important way for me to build stronger foundations in biology, computer science, mathematics, statistics, and machine learning.
This page is a small record of some of the online courses that shaped my training outside formal degree programs. I keep it here not as a complete transcript, but as a reflection of the habit of continuous learning that has accompanied my research career.
The first online course I completed on edX was “7.00x: Introduction to Biology - The Secret of Life,” taught by Eric S. Lander from MIT in 2013.
Since then, I have completed the following courses on edX and Coursera:
Programming
- An Introduction to Interactive Programming in Python (Rice University, Coursera, 2014)
- 6.00.1x: Introduction to Computer Science and Programming Using Python (MITx, edX, 2015)
- 6.00.2x: Introduction to Computational Thinking and Data Science (MITx, edX, 2015)
Machine Learning and Data Science
- DSE220x: Machine Learning Fundamentals (UCSanDiegoX, edX, 2018)
- 6.431x: Probability - The Science of Uncertainty and Data (MITx, edX, 2019)
- 18.6501x: Fundamentals of Statistics (MITx, edX, 2020)
- 6.86x: Machine Learning with Python-From Linear Models to Deep Learning (MITx, edX, 2020)
I also completed the three core courses of the MicroMasters Program in Statistics and Data Science offered by MIT on edX (record).
Course Reflection
Among these courses, 18.6501x: Fundamentals of Statistics was one of the most challenging and rewarding. Under the excellent instruction of Prof. Philippe Rigollet and with the help of the teaching assistants, I learned a great deal.
A memorable moment from that course appeared on the discussion board and stayed with me for a long time, partly because it reminded me of a scene from Good Will Hunting:
