Given that machine learning will make up the overwhelming majority of software development and that non-technical people will be exposed to AI systems more and more, one of the main challenges of AI is adapting and enhancing employee skills. It is also becoming necessary to support teaching staff in proactively taking AI's ethical and critical issues into account.
As an open-source company democratizing machine learning, Hugging Face believes it is essential to educate people from all backgrounds worldwide.
We launched the ML demo.cratization tour in March 2022, where experts from Hugging Face taught hands-on classes on Building Machine Learning Collaboratively to more than 1000 students from 16 countries. Our new goal: to teach machine learning to 5 million people by the end of 2023.
This blog post provides a high-level description of how we will reach our goals around education.
🗣️ Our goal is to make the potential and limitations of machine learning understandable to everyone. We believe that doing so will help evolve the field in a direction where the application of these technologies will lead to net benefits for society as a whole.
Some examples of our existing efforts:
🗣️ We want to lower the barrier to becoming a machine learning engineer by providing online courses, hands-on workshops, and other innovative techniques.
Apart from those efforts, many team members are involved in other educational efforts such as:
🗣️ We want to empower educators with tools and offer collaborative spaces where students can build machine learning using open-source technologies and state-of-the-art machine learning models.
We provide to educators free infrastructure and resources to quickly introduce real-world applications of ML to theirs students and make learning more fun and interesting. By creating a classroom for free from the hub, instructors can turn their classes into collaborative environments where students can learn and build ML-powered applications using free open-source technologies and state-of-the-art models.
We’ve assembled a free toolkit translated to 8 languages that instructors of machine learning or Data Science can use to easily prepare labs, homework, or classes. The content is self-contained so that it can be easily incorporated into an existing curriculum. This content is free and uses well-known Open Source technologies (🤗 transformers, gradio, etc). Feel free to pick a tutorial and teach it!
1️⃣ A Tour through the Hugging Face Hub
2️⃣ Build and Host Machine Learning Demos with Gradio & Hugging Face
We're organizing a dedicated, free workshop (June 6) on how to teach our educational resources in your machine learning and data science classes. Do not hesitate to register.
We are currently doing a worldwide tour in collaboration with university instructors to teach more than 10000 students one of our core topics: How to build machine learning collaboratively? You can request someone on the Hugging Face team to run the session for your class via the ML demo.cratization tour initiative.
🔥 We are currently working on more content in the course, and more! Stay tuned!
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