Data Science For All

Data Science—understood broadly as a merger between computation, statistics, data management and real-world applications—permeates through every sector of modern society. Innovative companies are developing data products galore, creating wealth and changing our daily habits: how we shop, how we commute, how we learn. Beyond products, algorithms are used to feed us advertisement and “news,” marshal police patrols in line to crime predictions, and even select the “right” employee for a position. Automatic systems are judging us. And not only do they reflect the inequalities of society, they can inflame our differences. In this new world, every citizen needs data-science literacy. UC Berkeley is leading the way on broad curricular immersion with data science, and other universities will soon follow suit. The definitive data-science curriculum has not been written, but the guiding principles are: computational thinking, statistical inference, and making decisions based on data. “Bootcamp” courses don't take this approach, focusing mostly on technical skills (programming, visualization, using packages). At many computer science departments, on the other hand, machine-learning courses with multiple pre-requisites are only accessible to majors. The key of Berkeley’s model is that it truly aims to be “Data Science For All.”