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Best way to learn math and programming

Long-term mentors and tutors for math and programming to help kids get into the best universities. To grow with kids from years 7 to 12.

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Free lessons for US$140 credits for new students!

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Learning Key Ideas by Programming

hand writing recognition using machine learning

“What I hear, I forget. What I see, I remember. What I do, I understand.”

NM pioneers this new breakthrough in math teaching: we teach children to code up the math concepts and apply them to solve engineering problems. After graduation from our courses, kids will be able build applications like the following: use Artificial Intelligence to recognize hand written characters.

NM Education takes a different approach to teaching mathematics and computer programming to children. We do not ask students to mechanically repeat exercises. They may be able to finish homework but they may not have the insights into the math concepts and understand why things are the way they are. We neither teach syntax and constructs of a computer programming language nor ask students to write useless toy code.

Our unique teaching methodology emphasizes learning-by-doing. For instance, the best way to understand homeomorphic function is to create your own and try to find its inverse. The best way to learn computer function is to code and run one. Therefore, the best way to learn mathematics and computer programming is to actually code a math function and programmatically find its inverse, hence math-programming! Once the kids can do the coding of the math, they will have a deep understanding of both the math and the programming.

NM Education has been developing a proprietary series of fun and challenging study materials that encourages students to think in terms of math models and computer algorithms in their daily life. This course’s pinnacle is when students develop an app to apply Artificial Intelligence and math to solve an engineering problem.

Lessons by Kids for Kids


Prof. Haksun Li

Prof. Haksun Li

Haksun holds a bachelor's degree in mathematics and a master's degree in financial mathematics from the University of Chicago, as well as a master's and a doctoral degree in computer science and engineering (with specialization in A.I.) from the University of Michigan, Ann Arbor.

Haksun worked as a quantitative analyst and a quantitative trader at UBS and BNP Paribas. Haksun, as an adjunct professor, has taught mathematics at many world-renowned universities including the National University of Singapore, Nanyang Technological University, Hong Kong University of Science and Technology, and Fudan University.

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