Jonathan Barrios: Data Scientist, AI Educator & Author
Jonathan Barrios is a data scientist, AI educator, and author specializing in artificial intelligence, machine learning, data science, and deep learning. Since 2019, he has taught at leading online platforms such as Treehouse, Thinkful, and currently at CBT Nuggets, where he designs and teaches comprehensive curriculum spanning foundational Python and data analysis with Pandas, NumPy, Matplotlib, and Seaborn, through advanced model building with TensorFlow, PyTorch, and Keras, into modern AI applications including prompt engineering, agentic coding, large language models, and LangChain-based agents. He also develops certification preparation tracks for the AWS Certified AI Practitioner, CompTIA Data+, CompTIA DataAI (formerly DataX), and ISACA Data Science Fundamentals (ITCA).
Barrios started programming games at age 12 but formally began his career as a music teacher before transitioning into full-stack web development to support online music education, eventually working as a developer at All Classical Portland radio. In 2008, his interest in machine learning was sparked by Andrew Ng's Stanford CS 229 course and Ray Kurzweil's The Singularity is Near, a fascination that reshaped his career trajectory. He brings this blend of music, programming, and AI to his teaching, employing a "zero-to-hero" methodology that makes complex technical concepts accessible to nontraditional learners and career switchers.
Barrios is the founder of Barrios AI, an initiative dedicated to Augmented Intelligence for Musicians, built on the philosophy that AI should augment human creativity rather than replace it. His first book, Artificial Intelligence for Musicians: From Kepler to Coltrane, traces the mathematical thread from cosmic harmonies to neural networks, teaching musicians and creatives how to guide AI as a tool for deliberate artistic exploration. Three more books are forthcoming: Prompt Engineering for Musicians, Vibe Coding for Musicians, and AI Practice Coach for Musicians.
Early Music Career
Earlier in his career, performing and composing as Jon Barrios, he was deeply rooted in Philadelphia's free improvisation scene. He co-organized the boundary-pushing Sci Fi Philly series at Gojjo with Dan Scofield, presented work at Bowerbird and The Rotunda, and collaborated with artists including Toshi Makihara, Dan Blacksberg, Jack Wright, John Dikeman, and Tatsuya Nakatani, alongside others connected to Peter Brötzmann and the Chicago/Luzern Exchange. He contributed to projects tied to the High Two label and the Shot x Shot collective, with support from Ars Nova Workshop.
After his father's passing, he stepped fully into his given name, Jonathan Barrios, carrying his father's spirit of contribution, learning, and exploration. Following a musical lineage that runs from Pythagoras and Kepler through Iannis Xenakis to John Coltrane, he is now developing this work at cosmoharmonics.com, formalizing a theoretical system he calls Cosmoharmonics. This system treats planetary motion data from NASA's Jet Propulsion Laboratory (JPL) as raw material, using data science and machine learning to create new harmonic structures, scales, and compositional systems from the movements of the solar system. Where Kepler heard the planets as "a continuous song for several voices, perceived by the intellect, not by the ear," and Xenakis built music from probability, sieves, and sound masses, Cosmoharmonics extends that mathematics-as-music tradition into the age of data science, turning orbital mechanics into continuous musical data structures and interactive compositions.
On the blog
Recent writing:
- Artificial Intelligence for Musicians — From Kepler's planetary harmonies to Coltrane, a guide to using AI to augment musicianship.
- Navigating Vibe Coding Safely — A framework for reviewing AI-generated code in production.
- Shaping the Future of AI — Takeaways from AI Conference 2023 in San Francisco.