AWS Machine Learning University

Educator enablement program prioritizing US community colleges, MSIs, and HBCUs

AWS Machine Learning University (MLU) now offers a free program helping community colleges, Minority-Serving Institutions (MSIs), and Historically Black Colleges and Universities (HBCUs) teach data management (DM), artificial intelligence (AI), and machine learning (ML) concepts. The program combines an educator enablement bootcamp with a rich curriculum to help institutions get course content and increase their teaching capacity to deliver courses on next-generation technology. It is expressly designed to address opportunity gaps by supporting students who are historically underserved and underrepresented in technology disciplines. MLU program content is available to all US colleges and universities, with priority consideration given to community colleges, MSIs, and HBCUs for the educator enablement component. The educator enablement bootcamps begin January 2023 and curriculum materials will be available in Spring 2023.

AWS Machine Learning University Educator Enablement

Benefits

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Educator enablement bootcamps

Participate in DM/AI/ML hands-on training through educator boot camps taught by AWS experts.

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Free compute resources

Get access to free compute resources and DM/AI/ML educational materials built by AWS MLU.

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A community of practice

Join the community to create cross-institutional partnerships and share DM/AI/ML technology updates.

Educator spotlight

The AWS Machine Learning University educator enablement program was sparked by a letter from Houston Community College (HCC) professor Dr. Raymond Brown to the AWS Machine Learning University team. Previously, Dr. Brown had adapted early versions of Machine Learning University’s videos, labs, and notebooks to help open the world of AI and ML to his students. HCC also received direct input from a cross-section of AI technology industry leaders, which, together with AWS’s Machine Learning University, contributed to HCC having built the first AI Associate of Applied Science degree program to be launched at a Texas community college. Through a pilot bootcamp, AWS has already trained 25 educators from 22 institutions to teach AI & ML through the MLU program.

"The early Machine Learning University content was so useful to me and really helped us to kickstart the AI program at Houston Community College. I’m thrilled that AWS is evolving the content and adding significant support for educators through the new educator enablement program. When it comes to AI, students are hungry to learn everything they can, there’s always something in AI that will interest anybody who touches it."

Dr. Raymond Brown, Professor - Houston Community College

How to get started

complete the form

Step 1: Complete the interest form

To get started, simply submit the online interest form.

get notified

Step 2: Receive program updates

Educators that complete the form will receive notifications about educator bootcamp dates and get access to DM/AI/ML educational materials.

attend a bootcamp

Step 3: Attend an educator bootcamp

Receive updates regarding upcoming educator bootcamps and join the waitlist. US community colleges, MSIs, and HBCUs will receive priority consideration.

Features

AWS Machine Learning University’s educator enablement program offers a suite of ready-to-use tools for educators including a library of modular AI/ML educational materials, free computing capacity, and comprehensive educator professional development built around MLU, Amazon's own internal training program for ML practitioners. The following AWS tools are made available for educators to leverage through the program:

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Machine Learning University

MLU provides access to the same machine learning courses used to train Amazon’s own developers on machine learning.

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AWS Academy

AWS Academy provides higher education institutions with a free, ready-to-teach curriculum that prepares students to pursue industry-recognized certifications and in-demand cloud jobs. This includes long-running hands-on lab environments where educators can bring their own assignments and invite their students to get experience using select AWS services and access to over 100 AWS services.

Amazon SageMaker Studio Lab

Amazon SageMaker Studio Lab is a free machine learning (ML) development environment that provides the compute, storage (up to 15GB), and security—all at no cost—for anyone to learn and experiment with ML. SageMaker Studio Lab accelerates model building through GitHub integration, and it comes preconfigured with the most popular ML tools, frameworks, and libraries to get you started immediately. 

AWS DeepRacer Student

AWS DeepRacer Student helps students develop their machine learning skills by going hands-on through the fun and excitement of autonomous RC car racing. Users can take advantage of 10 hours of monthly model training compute resources to up-level ML skills for free, while educators can leverage AWS DeepRacer Student community races to create private races and collaborative learning modules to fit their desired learning outcomes. 

Frequently asked questions

  • Q: What is it?

    The AWS Machine Learning University educator enablement program provides faculty at community colleges and universities with the necessary skills and resources to teach Artificial Intelligence and Machine Learning (AI/ML). The program prioritizes educator support for community colleges, Historically Black Colleges and Universities (HBCU), and Minority Serving Institutions (MSI) to make pathways to AI/ML jobs more accessible for a more diverse population of students.

    Q: Who can participate?

    The program is open to higher education institutions that offer accredited degrees, diploma, certificates, or continuing education programs who are planning to offer or extend an existing data management (DM), artificial intelligence (AI), and machine learning (ML) course, certificate or degree. We will prioritize community colleges, HBCUs, and MSIs for participation in educator enablement bootcamps.

    Q: What are the program offerings?

    We offer 1/ virtual educator bootcamps covering data management (DM), artificial intelligence (AI), and machine learning (ML) to build capacity to build and teach these courses. 2/ Ready-to-teach DM/AI/ML credit-worthy course and curricula built by AWS Machine Learning University and top educators. 3/ Free compute resources to enable educators and students to learn hands-on. 4/ A Community of Practice moderated by AWS Experts to create cross-institutional partnerships and share DM/AI/ML technology updates.

  • Q: How can I participate in an educator bootcamp?

    Faculty are encouraged to complete the interest form on this page to receive access to program resources and updates regarding upcoming bootcamps.

    Q: How much does it cost to participate?

    There is no direct cost for an institution/faculty member to participate. The program provides comprehensive, modular AI/ML content, free compute resources, comprehensive faculty training, and opportunities to attend professional development events.

    Q: I completed the interest form and have not been selected for a bootcamp yet. How are educators selected?

    Bootcamps are limited to 50 participants each session. Participation is prioritized for educators teaching at community colleges, HBCUs, or MSIs.

    Q: Am I eligible to participate in a bootcamp if I don’t teach Computer Science courses?

    Faculty members who are going to or plan to offer DM/AI/ML course as part of a certificate or degree can participate in the bootcamp. To ensure educators are set up for success, we recommend educators have basic Python programming knowledge.

    Q: Why should I/my institution participate in this program?

    Training students for AI/ML careers is an opportunity to accelerate students toward in-demand jobs and set them up for a path where continued growth is a real possibility. Those actively working in AI and providing technical inputs into AI applications earn salaries of $95,010.

    The purpose of this program is to bridge curriculum, time and resource gaps across higher education, putting the power to choose what will best serve the students at their college or university into the hands of educators themselves. By offering high-quality, ready-to-teach content and tools, teaching faculty are prepared to make AI/ML a part of their classrooms with minimal effort and set students up for high-paying, in-demand careers.

  • Q: How do I access the program curriculum?

    Courses will be available on AWS Academy and via SageMaker Studio Lab. Complete the interest form to receive additional information for accessing the content and getting started.

    Q: Does my school have to compete in a DeepRacer League in order to participate?

    No, schools are not required to participate in a DeepRacer League, however schools are encouraged to explore options to augment their learning. DeepRacer offers reinforcement learning content and a hands-on lab.