MOOC
As a firm believer in lifelong learning, I am grateful that MOOCs became widely available in 2012, making high-quality education accessible to almost everyone.
My top three favorite subjects are biology, computer science, and math. Bioinformatics, which combines these three fields, is particularly fascinating to me. MOOCs have provided a wonderful platform to systematically build the foundation of my knowledge in these areas.
The first MOOC 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 am also pursuing the MicroMasters Program in Statistics and Data Science offered by MIT on edX, which requires completing three core courses, one elective course, and a final capstone exam. I have finished the three core courses (record).
Course Reflection
The course 18.6501x: Fundamentals of Statistics has been the most challenging course I have taken since becoming a student. However, under the outstanding instruction of Prof. Philippe Rigollet and with the help of TAs, I learned a great deal. A memorable moment occurred on the discussion board during this course (reminiscent of a scene from the movie Good Will Hunting):
