Gain valuable ML skills with the AWS Machine Learning Engineer Nanodegree Scholarship from Udacity
Amazon Web Services is partnering with Udacity to help educate developers of all skill levels on machine learning (ML) concepts with the AWS Machine Learning Scholarship Program by Udacity by offering 425 scholarships, with a focus on women and underrepresented groups.
Machine learning is an exciting and rapidly developing technology that has the power to create millions of jobs and transform our daily lives. According to the Future of Jobs Report 2020 by the World Economic Forum, by 2025, 97 million new roles may be created as a result of ML innovation. However, only today’s developers have the skills to act on these opportunities now. Proximity to high-quality education, cost of traditional education, and allocating time to start and complete new learning projects make learning ML more complicated.
To address this challenge, AWS invests in educating developers, data scientists, and ML developers with a variety of education solutions, such as exploring reinforcement learning concepts with AWS DeepRacer, training and validation with the AWS Certified Machine Learning – Specialty certification, and hands-on tutorials from the AWS Machine Learning Community.
Up-leveling ML skills and opening new career opportunities
With the AWS Machine Learning Engineer Nanodegree by Udacity, developers can learn valuable skills for ML career path with an interactive, cost-effective, and accessible ML education. All students that enroll in the scholarship program have access to AWS Machine Learning Foundations, a free course covering an introduction to ML concepts, including reinforcement learning, computer vision, and generative artificial intelligence, with expert-led interactive tutorials with AWS AI Devices such as AWS DeepRacer, AWS DeepLens, and AWS DeepComposer.
The AWS Machine Learning Scholarship Program is open to all for registration starting May 26, 2021, through June 23, 2021. Your learning journey begins with the free AWS Machine Learning Foundations course on June 28, 2021, in which you learn the fundamental aspects of ML, ML techniques and algorithms, programming best practices, Python coding, and interactive tutorials with AWS AI Devices. You have 3months to study and complete your assessment by October 11, 2021, with the top 425 students eligible for a scholarship to the AWS Machine Learning Engineer Nanodegree.
The AWS Machine Learning Foundations Course (free) includes the following objectives:
- Learn the fundamentals of ML
- Learn object-oriented programming best practices
- Learn computer vision with AWS DeepLens, reinforcement learning with AWS DeepRacer, and generative AI with AWS DeepComposer.
- Dedicate 3–5 hours a week on the course and work towards earning one of the follow-up Nanodegree program scholarships
In the Machine Learning Engineer Nanodegree program (a $1,000 value course), you learn advanced ML techniques and algorithms, including how to package and deploy models to a production environment.
The AWS Machine Learning Nanodegree Program enabled me to learn and achieve valuable machine learning skills at my own pace with interactive modules that made learning fun and effective,” said Juv Chan, AWS ML Hero and AWS Machine Learning Nanodegree Program Alumni. “Carving out time to learn machine learning can be very hard, especially under the demanding schedules that software engineers work from. The flexibility offered by Udacity Nanodegrees lets me learn new skills on a timetable that works for me.”
This year, we added 100 additional scholarships on top of the 325 scholarships allocated in 2020, and updated the content for students with advanced ML techniques and algorithms and expert-led tutorials on deploying ML models at scale with Amazon SageMaker.
AWS is also collaborating with several nonprofit organizations through the We Power Tech Program to increase the diversity and talent in technical roles, including organizations like Girls In Tech and the National Society of Black Engineers. As part of these ongoing relationships, the nonprofit organizations will help encourage women and underrepresented groups to participate in the AWS Machine Learning Engineer Nanodegree Scholarship Program. Organizations like these develop programs to inspire, support, train, and empower people from underrepresented groups to pursue careers in tech.
“AWS strives to help level the playing field for women and people of color, who have been underrepresented in the tech industry for far too long. We are thrilled to collaborate with Udacity to make this sort of technical training more widely available and accessible,” said LaDavia Drane, global head of Inclusion, Diversity & Equity at AWS. “We look forward to seeing the incredible innovations in machine learning that are sure to come from this initiative.”
“Tech needs representation from women, BIPOC, and other marginalized communities in every aspect of our industry. Companies must make meaningful and measurable change in the areas of diversity, equity, and inclusion to reach their greatest potential, and skills training programs uniquely tailored to increase representation from these groups are necessary for technology to achieve all that it’s capable of. Girls in Tech applauds our collaborator AWS, as well as Udacity, for breaking down the barriers that so often leave women behind in tech. Together, we aim to give everyone a seat at the table.” Adriana Gascoigne, Founder and CEO, Girls in Tech.
How the AWS Machine Learning Engineer Nanodegree Scholarship works
Scholarship enrollment is open from May 26, 2021, through June 23, 2021. Students begin their learning journey with the AWS Machine Learning Foundations Course from June 28, 2021, through October 11, 2021. At the end of the course, learners take an assessment, from which top students are selected for 425 scholarships, who then start the AWS Machine Learning Engineer Nanodegree from October 25, 2021, through January 25, 2022.
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About the Author
Cameron Peron is Senior Marketing Manager for AWS AI/ML Education and the AWS AI/ML community. He evangelizes how AI/ML innovation solves complex challenges facing community, enterprise, and startups alike. Out of the office, he enjoys staying active with kettlebell-sport, spending time with his family and friends, and is an avid fan of Euro-league basketball.