This Udacity Nanodegree program graduate enacted a full-scale career change to become a Machine Learning Engineer.
Meet Robin Stringer. Robin worked as a journalist, a translator, and a marathon race guide for visually-impaired athletes, before a conversation about coding caused him to reevaluate his long-term career plans.
While he was working for a para-athletics non-profit in New York, he began learning Python online, and in the course of doing so discovered Udacity’s programs. He moved to Seattle and took the opportunity to pursue his coding studies full-time, with the goal of pulling off an audacious career change. After studying some of Udacity’s free courses, he started the Self-Driving Car Engineer Nanodegree program and got his first taste of machine learning. After a lot of work, he successfully landed a full-time role as a machine learning engineer.
We chatted with Robin to learn how he made his career change happen.
We talk with Dan Romuald Mbanga, Global Lead of Business Development for Amazon AI, about teaching students to use SageMaker for training and deploying deep learning models.
Deep Learning is one of the most exciting technology fields in the world today, and because Udacity’s learning platform is built to allow for maximum adaptability, our Deep Learning Nanodegree program is one of our most dynamic and future-facing programs right now, as we continue to respond to advances in the field by augmenting and enhancing our curriculum.
We are very excited to share details about the latest additions to our program curriculum, which include new content and projects focused on PyTorch and SageMaker. In a recent post by Cezanne Camacho, Curriculum Lead for Udacity’s School of Artificial Intelligence, we discussed new PyTorch content, and today, we’re going to explore how we’ll be teaching students to use SageMaker for training and deploying deep learning models.
To integrate the incredible new content, we teamed up with AWS and the SageMaker team, and in the updated program, students will train and deploy a sentiment analysis model on SageMaker, then connect it to a front end through an API using other AWS services. After deploying a model, students will also learn how to update their model to account for changes in the underlying data used to train their model—an especially valuable skill in industries that continuously collect user data.
To provide a closer look into the world of SageMaker, we spoke recently with Dan Romuald Mbanga, Global Lead of Business Development for Amazon AI, and a leader of business and technical initiatives for Amazon AI platforms.
In just two years, Ricardo Diaz executed an almost impossibly rapid career transformation. Today, he has a new career as a Machine Learning Engineer in Peru, and this is his story.
Ricardo Diaz is a machine learning engineer. He works for a great company in Peru, and he’s a graduate of no less than four Nanodegree programs! By all measures, he’s a success. But just two years ago, it was a different story. He was still in Venezuela, struggling to learn new skills. He was short of money, and his prospects for making a full-time salary weren’t great.
How did he manage such a rapid and complete career transformation? We chatted with Ricardo recently to find out.
Earn a scholarship from Facebook and Udacity, and learn how to build, train, and deploy state-of-the-art deep learning models with PyTorch. Apply today!
Today, we’re pleased to share details of our newest offering to rapidly expand students’ machine learning skills —the PyTorch Scholarship Challenge from Facebook.
PyTorch is an open source deep learning framework that’s quickly become popular with AI researchers for its ease of use, clean Pythonic API, and flexibility. With the preview release of PyTorch 1.0, developers can now seamlessly move from exploration to production deployment using a single, unified framework.
This new scholarship program, announced today at the PyTorch Developer Conference, offers participants the opportunity to acquire cutting-edge skills in deep learning using PyTorch, and earn a full scholarship to Udacity’s Deep Learning Nanodegree program.
Gil Akos knew the idea was a good one. He knew the product was something the world needed. But he didn’t have the skills yet to make it a reality. Four Nanodegree programs later, and Astra is live!
Gil Akos had an incredible idea for a new app. He wanted to empower individuals to make better decisions about their money through the power of technology. Gil believed that through smart financial modeling, based on deep learning, he could give people the power to make smarter moves with their money.
There was just one problem. Gil’s background was in architecture, not artificial intelligence. While his self-taught programming experience could get him so far, he lacked the skills to turn his app into reality. So Gil set out to master the skills and tools he needed. He found Udacity, and enrolled in the Machine Learning Engineer Nanodegree program. Now, two years later, his new iOS app—Astra—has officially launched, and Gil has graduated from four (and a half!) Nanodegree programs that he took to learn the skills he needed to bring his app idea to life.
We spoke to Gil to hear about his story.
The 2018 AI Challenger Global AI Contest is being co-organized by Sinovation Ventures—along with Sougo, Meituan-Dianping, and Meitu—and it features 10+ brand-new datasets, and a $450,000 USD prize.
In September of 2017, as an exclusive global education partner, Udacity had the pleasure of announcing details of a new AI competition and open data initiative organized by Sinovation Ventures. The event was entitled the AI Challenger Global AI Contest, and as Udacity COO Clarissa Chen noted in her contest announcement, “Artificial Intelligence has hit fever pitch in China. From cutting-edge tech powerhouses to established large corporations, everyone is setting up new AI Labs, hiring new talent, and announcing new platforms. “AI First” is the order of the day in China, and the excitement around this transformational technology is incredible.”
Success in 2017
The energy around AI across China was indeed incredible, and the subsequent success of the competition was clear evidence that it had been a perfect time to launch this kind of effort. Approximately 9000 teams from more than 60 different countries participated in the AI Challenger Global AI Contest, in 2017, and as reported by China Daily at the conclusion of the competition:
“AI Challenger released over 300,000 image-based as well as over 10 million language-based data entries to talents working on new technologies that will help AI applications ‘see’ and ‘read’ our world better.”
The 2018 AI Challenger Global AI Contest
China continues to represent a remarkable nexus for global AI innovation, and the 2018 AI Challenger Global AI Contest returns bigger, broader, and with more data than ever. As with last year, Udacity is especially pleased to be an exclusive global education partner, and we are excited to extend our ongoing collaboration with Sinovation Ventures to include new courses developed specifically to support contest entrants.
The Machine Learning community is busy sharing new research and insights on Twitter, and this is an extensive list of recommended AI researchers and pioneers to follow.
Artificial intelligence is advancing at a rocket’s pace, and every year the field looks fundamentally different than the year before. It’s often difficult to keep up with all the news and exciting results. The best way I’ve found is to follow the machine learning community on Twitter. This community lives on Twitter, sharing new research and insights, opinions, jokes, and just generally supporting each other. Keeping track of advancements in AI is not only fun but will also help in interviews by demonstrating to hiring managers your investment in the field.
To get you started following the machine learning community, here’s a fairly extensive list of AI researchers and pioneers I’m following.