Problem 5 is a lot of fun (well, “fun”) because (1) there’s a very simple program requiring no math that calculates the answer, but (2) that program would need impossible amounts of compute to actually run, and (3) you can figure the answer with pen and paper super fast if you think about the math a bit.

Project Euler problem 4 feels like a step back in difficulty. The numbers involved aren’t too big so we don’t have to worry about resource constraints. The subproblems it breaks down into are fairly straightforward.

Problem 3 is where Euler starts forcing us to consider resource limitations. Before, the most straightforward solution worked just fine, even if it used more resources than a less complex algorithm would.

Our first, and certainly not our last, encounter with the Fibonacci Sequence on Project Euler. Before we dive into Problem 2 together take some time to chew on it yourself if you haven’t already.

This is a lovely problem to start with. It has a straightforward brute-force loop solution as well as a nice analytic solution where you can calculate the solution directly without the need for much programming.

I’m working to scale one-to-one learning.

In 1984 Benjamin Bloom described the “
Two Sigma Problem", noting that students tutored with one-to-one techniques performed **two standard deviations better** than students in a traditional class.

He also dismissed large-scale one-to-one learning as “**too costly**” and **not “realistic**".

I believe Bloom was right about the effectiveness of one-to-one learning, but wrong about scalability. I’m building tools to prove that **scalable, accessible one-to-one learning is possible today**.