In the past few years, more data has been produced than in the millennia of human history before. This data represents a gold mine in terms of commercial value and also important reference material for policy makers. But much of this value will stay untapped — or, worse, be misinterpreted — as long as the tools necessary for processing the staggering amount of information remain unavailable.
In this article, we’ll look at how machine learning can give us insight into patterns in this sea of big data and extract key pieces of information hidden in it.
Over the course of an hour, an unsolicited email skips your inbox and goes straight to spam, a car next to you auto-stops when a pedestrian runs in front of it, and an ad for the product you were thinking about yesterday pops up on your social media feed. What do these events all have in common? It’s artificial intelligence that has guided all these decisions. And the force behind them all is machine-learning algorithms that use data to predict outcomes.
Now, before we look at how machine learning aids data analysis, let’s explore the fundamentals of each.
Machine learning is no longer a sci-fi concept, but an actual application of AI technology we use every day. Machine learning engineers focus on developing computer programs that can access data and use it to learn themselves.
Their daily work involves helping machines learn by creating and fine-tuning training datasets, developing machine learning models, and testing these datasets and models on machines. The goal is for the machine to be able to make informed decisions without the direct instruction of a human.
In line with our mission to train the world’s workforce in the careers of the future, Udacity is thrilled to announce brand new training programs with Microsoft to help professionals learn highly coveted skills with Microsoft. This collaboration kicks off with the Machine Learning Scholarship Program for Microsoft Azure, opening today, through which students will have an opportunity to earn a scholarship to the new machine learning Nanodegree program with Microsoft Azure.
As industries grow more reliant on technology and the skills needed to meet their new and changing demands, a new job category has emerged: new-collar jobs. IBM CEO Gini Rometty introduced the term “new-collar jobs” to refer to the in-demand technical skills that are obtained through vocational training, like Udacity’s Nanodegree Programs, opposed to a traditional four-year college.
During this unprecedented time of COVID-19, we’re experiencing more job loss than ever before. New-collar jobs offer an accessible and valuable way for workers to quickly break into tech-focused industries that offer stable careers with a lot of growth potential.
Graduating from a Nanodegree program is no small feat and definitely an accomplishment worth celebrating. One of our students, David Hundley, has recently graduated from his 10th Nanodegree program, and is now working on his 11th!
In just over a year, he was able to use the skills he learned across different Nanodegree Programs to transition into a Machine Learning Engineer role. Here’s David’s story: