Building fast and highly performant data science applications requires an intimate knowledge of how data can be organized in a computer and how to efficiently perform operations such as sorting, ...

If you rotate an image of a molecular structure, a human can tell the rotated image is still the same molecule, but a machine ...

Learn when and how to use different data structures and their algorithms in your own code. This is harder as a student, as the problem assignments you'll work through just won't impart this knowledge.

Machine-learning algorithms use statistics to find patterns in massive* amounts of data. And data, here, encompasses a lot of things—numbers, words, images, clicks, what have you.

More broadly, the algorithm offers a nice lesson in the power of cross-pollination between technology and academia -- a link that Google, of course, has embodied from the start.