Amazon Internal Machine Learning Courses are available to the Public
The Machine Learning University of Amazon makes its online courses open to the public. Classes that were previously only open to Amazon workers will now be accessible to the community.
Machine Learning University idea came from the fact that Amazon had a difficult time finding enough people with ML skills to meet their needs. Universities can't develop students with ML skills fast enough for Amazon, much less for all the other companies out there.
The first three online courses cover natural language processing (NLP) computer vision and tabular data (machine learning associated to tables and spreadsheet-like datasets).
A class in Machine Learning University (MLU) is created to address a specific business problem, such as in computer vision, or natural language processing and to help developers get their hands dirty very quickly in the areas that will provide an opportunity to apply machine-learning concepts to solve business problems.
MLU's courseware will develop and improve over time based on feedback from the builder community, similar to other open-source projects.
In terms of how people will take these lessons, AWS want to be flexible.
To get all of the new lessons, you can subscribe to the Machine Learning University YouTube channel and subscribe to the Amazon Science YouTube channel to learn about the work being performed by scientists to bring products and services to life at Amazon and AWS.
According to Amazon, there are currently three accelerated online courses available and they will continue to expand to include nine more in-depth courses before the end of the year. All MLU classes will be available via on-demand video, along with related coding materials, starting in 2021.
This field isn’t limited to individuals with advanced science degrees, or technical backgrounds. This initiative to bring our courseware online represents a step toward lowering barriers for software developers, students and other builders who want to get started with practical machine learning.Brent WernessAWS research scientist
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