First Steps

This is the very first track of the whole discipline, and it asks nothing of you but curiosity. A notebook, it turns out, is a conversation: you type a small instruction into a box called a cell, press run, and Python answers on the line below. That loop — type, run, read — is the single skill this track teaches, and it is the one every later module quietly reuses.

Here is the whole experience in ten seconds. Type 2 + 2 into a cell, press run, and 4 appears on the line below — no surprise, and that is the point: the only new thing is the pressing, not the sum. Now type your own name, in quotation marks, and press run again. Something comes back — but is it an answer, an echo, or a complaint? And what changes if you leave the quotation marks off? You could wonder about it, or you could be in the first module thirty seconds from now, watching what actually happens.

Three short modules carry you through it. In the first you run real Python and find it behaves like a calculator you can talk to — you predict the answer, press run, and check yourself. In the second you learn to ask the machine to show you things with print, and to read what it shows, because most of using a notebook is reading. In the third you deliberately break something — a missing quote mark, a misspelled word — so you can discover the best-kept secret of this whole discipline: an error is not a crash or a judgement, just the machine telling you, in a readable sentence, what it needs.

That last part matters more than it sounds. If your working material is language, you already have the one skill errors require: careful reading. The people who freeze at a red message are not missing talent — they were never told the message is addressed to them, in something close to English, and always names the line to look at. Once you have broken a cell on purpose and calmly fixed it, nothing later in this platform can make you feel lost.