AI Decoded: Inside Neural Networks

The Challenge: Demystifying "The Black Box"

AI education for youth often stays on the surface—teaching prompt engineering without explaining the underlying mechanics. For iUrban Teen, the goal was different. We needed to get past the prompts and break down how a Neural Network actually processes data.

I needed to explain complex concepts like Input Layers, Hidden Layers, and Back-propagation to middle and high schoolers in a 50-minute sprint without relying on heavy mathematics or coding.

The Solution: The "Human AI" Simulation

I designed an "unplugged" curriculum where students stop being passive users and become the algorithm.

Neural Node Operations

The session breaks the class into specialized "Node Teams" (Subject, Setting, Vibe, Style). These teams simulate the processing layers of a real machine learning model:

• Structured Processing: Teams use physical worksheets to decode visual data into specific parameters.
• The Generation Phase: Student-led inputs are fed into a live AI generator to produce immediate results.
• Iterative Learning: Much like real "Back-propagation," students analyze errors in the output and "re-train" their logic to improve the next generation.

Program Enablement Kit

To make sure this program could scale and actually hit the mark, I built out a full resource suite for educators and students:

• Interactive Presentation: A visual anchor designed for high engagement and energy not just lecture mode.
• Operational Worksheets: Structured docs that walk the "node" teams through their specific logic layers step by step.
• AI Literacy Survival Kit: A takeaway guide containing ethical frameworks, prompt structures, and verified AI resources.

Strategic Impact: Learning Ops in Action

This project shows what Learning Operations can achieve. It demonstrates the ability to translate high-level technical systems into scalable, actionable training programs.

• Complex System Mapping: Proved that advanced ML concepts can be taught through physical systems and collaboration.
• Technical Storytelling: Used metaphors (like "Human Nodes") to create a lasting mental model of how AI works.
• Digital Agency: Shifted how students see AI from something that feels like magic to a structured system they can understand and control.