周玮晨(Zhou Weichen)

Education

2022 ~ Now: Master of Computer Science (Network Technology), Universiti Kebangsaan Malaysia.
2014 ~ 2018: Bachelor of Management, Accounting (ACCA), East China Jiaotong University.

Related MOOCs I took

Programming:

• Introduction to Computer Science and Programming Using Python, edX, MIT 6.00.1.
• Introduction to Computational Thinking and Data Science, edX, MIT 6.00.2.
• CS 61A: Structure and Interpretation of Computer Programs, UC Berkeley.
• From Nand to Tetris: building a Mordern Computer From First Princeples, Hebrew University.
• Computational Structures, 6.004, MIT.
• CS 61B: Data Structures, UC Berkeley.
• Algorithms, Princeton University.
• CS106B: Programming Abstruction, Stanford University.
• CS144: Introduction to Computer Networking, Stanford University.
• Introduction to Theory of Computation, Neso Academy.

Machine Learning:

• Machine Learning, Coursera, Stanford University.
• Machine Learning, Hung-yi Lee.
• Dive into deep learning.

Math and Stats:

• Linear Algebra, Hung-yi Lee, National Taiwan University.
• Probability - The Science of Uncertainty and Data, edX, MIT 6.431x.
• Fundamentals of Statistics, edX, MIT 18.6501x.
• Linear Algebra, 18.06, MIT

Skills

• English Proficiency: IELTS 6.0/9.
• Programming Languages: Java, C++, Python and could use Python packages including Pytorch, Numpy, pandas.

Related books I read

• Introduction to the Theory of Computation (3rd Edition). Michael Sipser.
• Computer Networking: A Top-Down Approach (7th Edition). Jim Kurose, Keith Ross.
• The Elements of Computing Systems. Noam Nisan, Shimon Schochen.
• SICP in Python. UC Berkeley.
• Python Data Science Handbook. Jake VanderPlas.
• Algorithms (4th Edition). Robert Sedgewick, Kevin Wayne.
• Linear Algebra and Its Applications (5th Edition). David C. Lay, Steven R. Lay, Judi J, McDonald.