MOOC
As a firm adherent of lifelong learning, I really appreciate that MOOCs became available for almost everyone in 2012.
Biology, computer science and math are the top 3 subjects of my favorite. Bioinformatics is an interdiscipline associated with these three subjects. MOOCs give me a wonderful platform to construct the foundation of my knowledge network systematically.
The first course I finished at Edx taught by Eric S. Lander from MIT: 7.00x: Introduction to Biology - The Secret of Life in 2013.
Since then, I learned the following courses at Edx and Coursera.
Programming
- An Introduction to Interactive Programming in Python (Rice University at Coursera, 2014)
- 6.00.1x: Introduction to Computer Science and Programming Using Python (MITx at Edx, 2015)
- 6.00.2x: Introduction to Computational Thinking and Data Science (MITx at Edx, 2015)
Machine Learning and Data Science
- DSE220x: Machine Learning Fundamentals (UCSanDiegoX at Edx, 2018)
- 6.431x: Probability - The Science of Uncertainty and Data (MITx at Edx, 2019)
- 18.6501x: Fundamentals of Statistics (MITx at Edx, 2020)
- 6.86x: Machine Learning with Python-From Linear Models to Deep Learning (MITx at Edx, 2020)
MicroMasters Program in Statistics and Data Science provided by MIT at Edx needs to finish 3 core courses, 1 elective course and a final capstone exam. I have finished 3 core courses (record) and I am going to take the last course and final exam in the next round.
18.6501x: Fundamentals of Statistics is the hardest course I have ever taken since I became a student. But I really learned a lot under the outstanding teaching of Prof. Philippe Rigollet and the help of TAs. There was an very interesting episode on the discussion board during this course (please watch movie Good Will Hunting):
