From the start, industry partnerships have played an important role in the development of our Self-Driving Car Engineer Nanodegree program, and these partnerships are an integral part of the program’s groundbreaking success.
Hiring partnerships with industry leaders such as Mercedes-Benz, NVIDIA, BMW, and Bosch enable us to achieve our goal of directly connecting learning to jobs, and the companies with whom we develop our world-class curriculum help us ensure our students are mastering the most valuable skills in the industry.
Announcing new Elektrobit content
Today, we’re extremely excited to announce that Elektrobit, one of our program’s hiring partners, will now be contributing content for the program as well! Elektrobit is a leading developer of embedded and connected technology solutions for the automotive industry, and will be developing program content on automotive functional safety.
We’re excited to announce the start of a new scholarship program designed to provide learning opportunities for recipients to make the world a better and safer place for everyone.
In the case of this very special scholarship, we also have the opportunity to honor the great work of our partner, Liam’s Life Foundation. Last week, three students started studying in the Self-Driving Car Engineer Nanodegree program. Each of them is receiving a full scholarship to the program, in honor of Liam Mikael Kowal, a 15-month old toddler who was struck and killed by a drunk driver in Southern California in September 2016. Though drunk driving is preventable, a person loses their life to a drunk driving accident every 53 minutes. This amounts to 28 people a day and nearly 10,000 people a year in the United States alone.
We officially have the opportunity of a lifetime for you.
You’ve heard about self-driving cars. You’ve read about self-driving cars. Depending on where you live, you may have even seen them driving themselves around. You may also know Udacity teaches people to become Self-Driving Car engineers. We even have our own self-driving car, and our students are contributing actual code! That’s right. We are building the world’s first open-source self-driving car. Our program is groundbreaking in every sense of the word—there’s no other opportunity quite like it out there.
Today, you can find out what all the excitement is about. Yes, you. Everyone. Every single person in the entire world is invited into our Self-Driving Car Nanodegree program classroom for a free sneak preview!
Experience the Self-Driving Car Nanodegree Program classroom today!
Intersect 2017 is now behind us, but we’re still buzzing with excitement! It was such an incredible meeting of so many minds, and a living testament to the power of community. With the theme of Learning for the Jobs of Today, Tomorrow, and Beyond to rally around, you could just feel new opportunities emerging, and great connections were being made everywhere you looked.
It is with this theme front-of-mind that we’ve recently been featuring stories about Udacity students getting jobs—specifically, our Self-Driving Car program students, because in many ways, their stories are emblematic of the fact that the jobs of tomorrow are already becoming the jobs of today.
Our Intersect 2017 conference is but a few weeks away now, and as we draw closer to the big event, we continue to think through the implications of the theme we’ve chosen: Learning for the Jobs of Today, Tomorrow, and Beyond. As detailed in a previous post, we’ve found ourselves thinking quite a bit about our Self-Driving Car Nanodegree program students in particular, as in many ways their paths seem emblematic of what this theme is all about, especially the “jobs of tomorrow” part.
As it turns out, however, Self-Driving Cars as an employment field is very much a “jobs of today” space, as evidenced by how many of our current students are already finding jobs! We’re honored to highlight a number of these stories and share them with you, and today we feature Caleb Kirksey.
When we chose Learning for the Jobs of Today, Tomorrow, and Beyond as our Intersect 2017 conference theme, we were thinking about the journey from learning to a job at a fairly high level, as we wanted to embrace something that would resonate through every aspect of the conference.
Once the planning stages were largely behind us, we were able to really start looking at the meaning of this theme at eye-level, and thinking about what it means to each individual student.
We found ourselves in particular thinking about our Self-Driving Car Engineer Nanodegree program students, as in many ways they are preparing themselves for an industry that is still in the imagination stages! Self-driving cars are coming. We know this, as do our students. But the roles they’re now preparing for truly are the jobs of tomorrow.
Or are they?
Artificial intelligence. Machine learning. Self-driving cars. If you’re keeping up with the rapid changes in the technology industry, you’re seeing a bunch of terms thrown around as if they’re interchangeable—but really, there are some pretty important distinctions. In this post, we’re going to demystify the differences, and clarify the relationships, among these terms, especially artificial intelligence, machine learning, and self-driving cars. Let’s begin with a simple model for how we’ll approach this topic:
Artificial intelligence is the ‘what’.
Machine learning is the ‘how’.
Self-driving cars are the ‘why’.