Machine Learning Engineer
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In this program, you’ll master valuable machine learning skills that are in demand across countless industries. Investment levels in this space continue to rise, thousands of highly-valued startups have entered the field, and demand for machine learning talent shows no signs of leveling. Program graduates emerge uniquely prepared to excel in machine learning roles.
Get started learning Machine Learning through interactive content like quizzes, videos, and hands-on programs. Our learn-by-doing approach is the most effective way to learn Machine Learning skills.
Advance quickly and successfully through the curriculum with the support of expert reviewers whose detailed feedback will ensure you master all the right skills.
Get free access to Amazon Web Services - the same platform used by Machine Learning Engineers around the globe - to build and deploy your models.
Receive personalized feedback from our expert Careers Team, to help you perfect your resume, refine your LinkedIn profile, and prepare for a Machine Learning interview.
The Machine Learning Nanodegree program is designed to ensure your long-term success in the field. The skills you learn will prepare you for jobs in machine learning, and you’ll be ready to deliver immediate value to any organization. We will support you throughout your learning journey; from gaining valuable technical and career skills, to landing your dream job.Designed to prepare you for career success in machine learning.
Machine learning experts are in high demand. Create your professional portfolio with Udacity and open up a world of opportunities. Our hiring partners are eager to meet you.Create your portfolio and open up a world of opportunities.
Work with experienced careers professionals for tailored advice on how to improve your search and impress recruiters. Including feedback on your LinkedIn, GitHub, and professional brand.Work with career professionals to impress recruiters
40,000+ highly-skilled grads make up your new career community. Ready to collaborate, share referrals, or hire your own team? The Udacity Alumni Network is here for you!Connect with our global community to grow your career.
Arpan is a computer scientist with a PhD from North Carolina State University. He teaches at Georgia Tech (within the Masters in Computer Science program), and is a coauthor of the book Practical Graph Mining with R.
Mat is a former physicist, research neuroscientist, and data scientist. He did his PhD and Postdoctoral Fellowship at the University of California, Berkeley.
Luis was formerly a Machine Learning Engineer at Google. He holds a PhD in mathematics from the University of Michigan, and a Postdoctoral Fellowship at the University of Quebec at Montreal.
Alexis is an applied mathematician with a Masters in computer science from Brown University and a Masters in applied mathematics from the University of Michigan. She was formerly a National Science Foundation Graduate Research Fellow.
Jay is a software engineer, the founder of Qaym (an Arabic-language review site), and the Investment Principal at the Riyad Taqnia Fund, a $120 million venture capital fund focused on high-technology startups.
As the founder and president of Udacity, Sebastian’s mission is to democratize education. He is also the founder of Google X, where he led projects including the Self-Driving Car, Google Glass and more.
Ortal Arel is a former computer engineering professor. She holds a PhD in Computer Engineering from the University of Tennessee. Her doctoral research work was in the area of applied cryptography.
It was an excellent start to learn ML. I enjoyed a lot.
Machine Learning Engineer Nanodegree program was an excellent experience for me.
There were parts of the program that were challenging. But all in all it was a very enjoyable and satisfying program and I feel it will help me further my career in machine learning.
Good in general. Just a little glitch that i faced last week : Non gpu environment for deep learning project was very flaky. I first intended to use non gpu mode to get started and handle the basics, without using gpu time for this basic part but the environment was so flaky that (connection drops, environment refresh, lost work) I had to switch to gpu, which costs you somewhat more money I guess:)
This is an interesting program. There are certain topics (tough to keep track of which ones exactly) that would be better understood if they are explained in more basic terms.
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Become a Machine Learning Engineer. Master skills by building models that solve real-world challenges.
Admissions Closes: 22 August, 2018
If you have successfully graduated from Term 1, then please email email@example.com to enroll in Term 2.
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