Spark curiosity. Spread knowledge. Inspire through hands-on experiments on fascinating topics.
Online Math-Programming classes for kids aged 10 - 17 years old.
Innovative approach to teach and learn mathematics using programming.
“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.
Topics
Algebra
Advanced Math
Visualization and Plotting
Probability and Chance
Data Analysis
Math Modeling
Physics
Math Thinking
A.I.
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. His last academic appointment is as an associate dean and professor of the Big Data Finance and Investment Institute of Fudan University.
