We’re excited to announce that Udacity and Amazon Web Services (AWS) Educate are teaming up to support our students as they go beyond learning AI, to actually building powerful AI models in the real world!
Starting on April 19, all Machine Learning Engineer Nanodegree program students are eligible for complimentary AWS Promotional Credits to explore AWS services, including Amazon SageMaker. This means that our students will be able to harness the incredible computing power of AWS to train and deploy machine learning models faster than ever, without having to worry about hardware.
AWS is the most successful cloud infrastructure company on the planet, and we’re thrilled to bring the power of their services to our students.
Democratizing Access to Compute Power
Not so long ago, machine learning progress was held back by the fact that you needed a really powerful computer to build your models. This requirement meant that far too many innovative minds were excluded from contributing knowledge and ideas. Today, the rise of AWS and cloud computing means that anyone with a laptop can harness the power of thousands of off-site machines.
No longer do you have to build your own supercomputer with a $3K Graphics Processing Unit (GPU). Instead, you can speed up your models 100x by using Amazon’s GPUs.
The Skills to Build
At Udacity, you learn by doing. You master complex technologies, learn challenging concepts, and solve real-world problems through completing hands-on projects. Students in our School of Artificial Intelligence programs do everything from building image classifiers that automatically recognize different dog breeds, to training quadcopters to fly using reinforcement learning.
We created this approach because we know it’s critical that our students have experience deploying their work on the same technologies that machine learning engineers all over the world use every day. Plus, we know our students are driven to make an impact, and engineers who combine passion and skills are exactly what leading companies are looking for.
How it Works
Your first and most important step is enrolling in our Machine Learning Engineer Nanodegree program. If you’re ready to enroll today, you can do so here. You can also explore a Free Preview. If you’d like to discover more about our comprehensive AI offerings, and understand where Machine Learning fits in, please visit our School of Artificial Intelligence.
Once you’re enrolled, you’ll start learning in the classroom right away. When you come to your first project submission, you’ll receive your details on how to claim your AWS credits, and create your AWS Educate account. In addition to your AWS credits, having an AWS Educate account gets you access to additional career resources, including exposure to relevant job opportunities from the AWS partner network via their job board.
In our Machine Learning Engineer Nanodegree program, students use AWS credits to launch GPU-enabled EC2 instances for multiple exercises and projects. These include a project focused on Convolutional Neural Networks, in which students build an algorithm that can correctly identify and classify dog breeds using real-world, user-supplied images.
A Long-Term Commitment to our Alumni Community
We’re especially thrilled that AWS is also providing extra credits to Machine Learning Engineer Nanodegree program students upon graduation. As you go out into the world and start applying your newfounds skills to cutting-edge challenges, you’ll continue to have access to one of the very best AI platforms in the world!
This long-term commitment to community is central to our approach at Udacity, and we know firsthand from our alumni how important the community experience is to their learning journeys:
“I loved learning alongside amazing students from a diverse range of backgrounds and industries. The community empowered me to drive innovation in the aerospace industry.” —Kamil K., Machine Learning Engineer Nanodegree program graduate, Donauwörth, Germany
Enroll by April 19th
If you’d like to experience a world-class machine learning education, and get access to the same best-in-breed tech stack that machine learning engineers all over the world use every day, then we invite you to enroll in out Machine Learning Engineer Nanodegree program today.
Enrollment for the next term closes on April 19th; enroll by the deadline, and start building and deploying your machine learning projects on AWS!