Updated: Apr 11
Learning AI is a great thing for students in elementary, middle, or high school. However, what platform should they learn on? What platforms and tools will enable them to build innovations that bring their imaginations to life. Which platforms can they continue to use as they get older? What technologies will help them get internships when they are in high school?
The most important things to factor in when choosing a learning platform are
Can my child get started with the coding knowledge they have? An ideal platform enables the child to learn with the platform - i.e. they can build AIs even if their coding knowledge is limited but be able to do more powerful things as their coding knowledge grows
Does the platform “fall off a cliff”? Any platform that is limited creates a “fall off a cliff” moment for a child. This is a problem for most toy tools including those that rely exclusively on kid-specific programming languages like Scratch. They are fun to use at the beginning, but once the child grows and advances, the tool is no longer effective, and using it did not help the child learn any real-world skills on professional tools.
Can they build anything they like? One of the great strengths of AI is that kids can solve real-world problems and create innovations that they can use for science fairs, competitions, and entrepreneurship. This usually requires that the platforms that they use accommodate real datasets (such as temperature data for climate change projects, MRI data for disease detection, text data for chatbots, and more). Real-world datasets also tend to be large, so the platform needs to accommodate the scale of these datasets.
Here are some common real-world platforms that professionals use to build AIs
SciKit Learn (also called sklearn). This is the most popular python package for AI - heavily focused on Machine Learning
Pandas and Numpy. These are the most popular professional packages used for processing datasets
TensorFlow. Originally created by Google - this is one of the most popular open source packages for Deep Learning and Natural Language Processing
AWS Sagemaker. This is Amazon Web Services’ flagship AI package - used on the AWS cloud by professionals
Google Cloud AI Platform. This is Google’s flagship AI package - used on the Google cloud by professionals
Any one of these would be valuable for kids to learn, but most are challenging to start with.
What we do at AIClub
AIClub has created Navigator as a transitional platform to help kids start with minimal or no coding knowledge and seamlessly transition to one or more of the professional tools listed above. The figure below shows how Navigator layers above the professional tools.