AWS Launches AI Program for Community Colleges, Minority-serving Institutions, and HBCUs
Dec. 2, 2022 — Amazon Web Services (AWS) Machine Learning University is now launching a free program helping community colleges, minority-serving institutions (MSIs), and historically Black colleges and universities (HBCUs) teach database, 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.
According to the Georgetown Center on Education and the Workforce, Black and Latino students earn bachelor’s degrees in engineering—the dominant pathway to AI/ML careers—at a much lower rate than their white peers, earning 4% and 13% respectively of such degrees. This is exacerbated by the fact that the institutions serving Black and Latino students often lack the resources to deliver courses in cutting-edge technologies. The most selective U.S. four-year colleges and universities, where white and Asian college students are concentrated, spend anywhere from two to nearly five times as much per student compared to less-resourced colleges and two-year colleges, where Black, Hispanic, and Latino students are often concentrated—deepening gaps in college opportunity.
The educator enablement bootcamp and curriculum is expressly designed to address these opportunity gaps by supporting students who are historically underserved and underrepresented in technology disciplines. The program is available to all U.S. colleges and universities, with priority consideration given to community colleges, MSIs, and HBCUs for the educator-enablement component. The educator-enablement bootcamps will start January 2023, and the curriculum materials will be available in spring.
The program was sparked by a letter from Houston Community College (HCC) professor Dr. Raymond Brown to Bree Al-Rashid, AWS’s Machine Learning University lead. Previously, 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.
“After that, 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 best community college AI associate degree program in the country,” said Brown. “We are proud and thankful to AWS and their continued support of the program curriculum development, faculty, and students.”
With Brown’s efforts and the content help from AWS, HCC is the first community college in Texas to launch an AI Associate of Applied Science degree program. HCC is building on these efforts and will be the first community college in the U.S. to offer a bachelor’s degree in AI in fall 2023, pending final approval from the Southern Association of Colleges and Schools Commission on Colleges.
Inspired by Brown’s resourcefulness and dedication to his students, AWS designed and built a turnkey teaching solution expressly for educational institutions, featuring a robust new curriculum and resources specifically created to help educational institutions increase their teaching capacity through an educator-enablement component. The program is a small-group virtual bootcamp—with live instructor-led lectures and hands-on projects—to introduce educators to the curriculum. In 2023, AWS plans to run six educator-enablement cohorts. Educators who complete the educator-enablement program will receive continuing education credits and an AWS stipend. They will also have access to year-round professional development opportunities, including tech talks, dedicated Slack study groups, virtual study sessions moderated by AWS instructors, and regional events.
The program builds on AWS’s original Machine Learning University which is designed to train Amazon employees, featuring the same courses Amazon uses internally. The educator enablement course materials, including lecture slides, hands-on coding exercises, exams, and instructor handbooks, were developed with feedback from school systems, including HCC, and the materials are designed to meet the requirements for college-level, for-credit courses. As part of the new educator enablement program, AWS also will provide free compute power to help students practice what they learn, apply AI and ML concepts, and experiment with a range of AWS services in a cloud-based sandbox, giving students hands-on experience with the most broadly adopted data, analytics, and ML cloud computing tools in the professional world.
“The early Machine Learning University content was so useful to me and really helped us to kickstart the AI program at Houston Community College,” said Brown. “I’m thrilled that AWS is evolving the content and adding significant support for educators through this new program.”
“Our goal in launching this program is to make database, AI, and ML education widely accessible to all community colleges and universities across the U.S.—not just elite institutions,” said Swami Sivasubramanian, vice president of Databases, Analytics, and Machine Learning at AWS. “We need the best minds from all backgrounds entering these fields. The educator enablement program is designed to make it easier for any educational institution to start teaching advanced technologies by removing the barriers of cost and educator training.”
The educator enablement program is part of AWS’s broader efforts to empower diverse communities to pursue tech careers. Last year, AWS launched the AI & ML Scholarship program to help prepare underserved and underrepresented students for careers in these disciplines. Through the scholarship program, AWS has helped more than 20,000 learners get hands-on with AI and ML technology and awarded 2,000 scholarships. AWS has collaborated with community colleges, MSIs, and HBCUs over the years, including a collaboration with Howard University to prepare students for in-demand cloud careers.
To register for the educator-enablement program or get notified about course content availability, click here.