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AWS Machine Learning University currently offers a free educator assistance program. The program teaches faculty at community colleges, minority-serving institutions (MSIs), and historically black colleges and universities (HBCUs) concepts in data analytics, artificial intelligence (AI), and machine learning (ML), providing them with the skills and resources to build a diverse pipeline for in-demand jobs now and in the future.
According to the National Science Foundation, Black and Hispanic or Latino students complete bachelor’s degrees in computer science, the primary pathway to AI/ML, at a much lower rate than white students, accounting for less than 11 percent of computer science degrees awarded. However, research shows that diverse perspectives among seasoned practitioners and across the AI/ML lifecycle contribute to the development of safe, reliable, and unbiased AI/ML systems.
In 2018, we announced Machine Learning University (MLU), which shares the same courses with all developers that we use to train engineers at Amazon and AWS. The platform offers self-service, self-paced AI/ML digital courses.
And today, we’re adding this new program to our AI/ML training offering. MLU’s self-paced learning is accessible to everyone, but the burden of sourcing prerequisite work and solutions is on the learner. This educator support program takes the concepts and lessons developed by MLU and makes them more accessible to educators. We offer year-round educator support programs, including access to lesson plans, course playbooks, and free computing resources.
Program details
Educators attend bootcamps in small groups where they learn the material and delve into its teaching methods through instructor-led lectures and hands-on projects. Educators who complete the bootcamp can participate in a variety of development opportunities throughout the year, including a dedicated Slack channel to share teaching best practices, education topic series and virtual learning sessions moderated by MLU instructors, and regional events for continued professional development. You will also receive continuing education credits and scholarships provided by AWS.
Instructors and students can access educational materials through Amazon SageMaker Studio Lab. SageMaker Studio Lab is a free (no credit card required) ML development environment on AWS that was announced last year. We provide compute and storage for people who want to learn and experiment with ML. Educational institutions can unlock additional resources to support their ML programs by enrolling in AWS Academy. AWS Academy unlocks all AWS services for a complete AI/ML program.
Community colleges and universities can integrate this educator assistance program into their computer science, information technology, or business curriculum to create AI/ML courses, certificates, or degrees. We have worked with educators and school boards, including Houston Community College, to create vetted content for credit and degree-earning curricula.
In August 2022, we launched our first educator bootcamp in partnership with a coding school. The bootcamp ran for two weeks and included lectures, case studies, and hands-on projects. Twenty-five educators representing 22 community colleges and universities in the United States completed the Educator Machine Learning Bootcamp.
Learn more and join the program
During 2023, AWS Machine Learning University will conduct six educator cohorts starting in January. The program will give priority consideration to community college, MSI, and HBCU educators, consistent with the program’s mission to increase access to AI/ML technologies for historically underserved and underrepresented students.
If you are a computer science educator or part of an educator committee interested in furthering your computer science teaching, you should sign up for the Educator Enablement Program.
— Marcia
