With big institutions like Harvard and MIT holding online classes, an interesting question to be raised is what will become of our future data scientists who learn from home, physically distant from fellow students?
If learning data science online is unavoidable, then perhaps it’s important to look at what matters most when learning data science: Real-world projects.
Real-world projects are where the rubber hits the road. A.I. projects serve a purpose, something bigger than the computations that comprise it. For this reason, it’s not enough to trivially understand what an algorithm does from the perspective of a textbook or Wikipedia. To accomplish a project, students must move from learning to application.
Imagine having a strong understanding of the fundamental computations that went into Google Assistant or Siri or Spotify song recommendations. These technologies are dizzying (and quite wonderful), but the tech is not the end result of the “project”. The end result is something that’s usable and requires little or no technical understanding.
It’s immensely difficult for a junior data scientist to create a project by applying algorithms they don’t understand at a deep level. For these reasons, when I look at a resume I’m much more interested in what someone’s done versus what they’ve learned to do. And students at all levels have access to online learning like never before. That’s a good thing.
Even with the biggest institutions moving classes online, I’m optimistic that motivated students will do what they’ve always done: use any opportunity to find projects that interest them and dive deeply into their own learning experiences.
Since much of data science involves data gathered online, and since we’re all at home a lot more lately, there are incredible opportunities to build cool stuff backed by data. And there are more ways than ever to find help learning.
Coursera (co-founded by the venerable Andrew Ng), just raised $130MM in their Series-F (I didn’t even know funding rounds went that far). They’ve received nearly a half-billion dollars in funding to grow their online learning platform.
Not to be outdone, Udemy is looking to raise money on a $3BB valuation, and enrollment for their classes has more than quadrupled from February to late March 2020, due in large to the pandemic.
With an unprecedented number of opportunities to learn data science and access free online datasets, those wanting to learn data science are limited only by their imaginations.
Can you Predict the Next President of the United States?
Did you know that the Obama campaign had a data analytics team of 100 people? Data analytics impacts the world profoundly, from recommending products to customers on e-commerce websites to electing powerful leaders. Data analytics has evolved to become the brain of every election campaign since the Obama campaign. Data analytics helps the election campaign to understand voters better and hence adapt to their sentiments. This article shows how data analytics affects elections and how election campaigns use it. Here’s a direct prediction of the American presidential election. And a much different approach here.
Only 18% of Data Science Students Learn About A.I. Ethics
Amid a growing backlash over A.I.‘s racial and gender biases, numerous tech giants are launching their own ethics initiatives — of dubious intent. The schemes are billed as altruistic efforts to make tech serve humanity. But critics argue their main concern is evading regulation and scrutiny through “ethics washing.” Read the article here and let us know what you think.
Citizen Data Scientists Needed to Save the Planet
This article shows a fascinating project to mobilize a small army of citizen data scientists to collect data with the aim to help train machine learning algorithms that will be embedded in a range of environment and healthcare applications. Take a look here. Can data science perhaps help save the planet?