Real-world projects from industry experts
With real-world projects and immersive content built in partnership with top-tier companies, you’ll master the tech skills companies want.
At 10 hrs/week
Get access to the classroom immediately upon enrollment
Learn foundational machine learning algorithms, starting with data cleaning and supervised models. Then, move on to exploring deep and unsupervised learning. At each step, get practical experience by applying your skills to code exercises and projects.
This program is intended for students with experience in Python, who have not yet studied Machine Learning topics.
In this lesson, you will learn about supervised learning, a common class of methods for model construction.
In this lesson, you’ll learn the foundations of neural network design and training in PyTorch.
In this lesson, you will learn to implement unsupervised learning methods for different kinds of problem domains.
Our knowledgeable mentors guide your learning and are focused on answering your questions, motivating you, and keeping you on track.
You’ll have access to Github portfolio review and LinkedIn profile optimization to help you advance your career and land a high-paying role.
Tailor a learning plan that fits your busy life. Learn at your own pace and reach your personal goals on the schedule that works best for you.
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Cezanne is a machine learning educator with a Masters in Electrical Engineering from Stanford University. As a former researcher in genomics and biomedical imaging, she’s applied machine learning to medical diagnostic applications.
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.
Jennifer has a PhD in Computer Science and a Masters in Biostatistics; she was a professor at Florida Polytechnic University. She previously worked at RTI International and United Therapeutics as a statistician and computer scientist.
Josh has been sharing his passion for data for nearly a decade at all levels of university, and as Lead Data Science Instructor at Galvanize. He's used data science for work ranging from cancer research to process automation.
Andrew has an engineering degree from Yale, and has used his data science skills to build a jewelry business from the ground up. He has additionally created courses for Udacity’s Self-Driving Car Engineer Nanodegree program.
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