The ideas behind data and AI, explained
Each of these takes one idea from the Data to AI course and explains it the way the course does: plainly, with an example you can picture, and with something to play with where it helps. No formulas you have to memorize. If one of them clicks, the course has three more lessons on it and twenty three more modules after that.
Mean vs. median: what’s the difference?
Why one billionaire makes “the average” lie, and when to use the median.
Correlation vs. causation: what’s the difference?
Ice cream doesn’t cause sunburns. How to tell a real cause from a coincidence.
What is standard deviation?
How spread out the numbers are, and what one and two standard deviations cover.
What is a digital footprint?
The trail of data you leave behind, most of it without typing a thing.
What is sampling bias?
Why who you ask changes the answer, and why twenty random beats two hundred convenient.
What is a database?
Tables, rows, IDs and why two Sams never get mixed up.
What is machine learning?
Teaching a computer with examples instead of rules, and how it goes wrong.
How does ChatGPT work?
Chunks in, one guess at a time out, and why it can sound sure and still be wrong.
Learn it by doing it
Data to AI is five-minute lessons on how AI works, starting with the data on your phone, for curious teens, parents and grandparents. No math needed. The first lesson runs right here in your browser.