The Coursework
Five engineering projects from AI: Principles and Application (4V98) — AI agents, automation workflows, machine learning models, a cinematic AI video, and a full-stack Django marketplace — plus a flagship SAP corporate sponsorship pitch built for S3E.
The flagship
Corporate Sponsorship Pitch • S3E Program • Spring 2026
Baylor Athletics × SAP
Partnership Proposal
An executive-grade partnership pitch built as a 7-page interactive website — jersey patch sponsorship, premium suite activations, a keynote series, a custom AI fan app, and a Playfly-powered measurement framework. Includes an embedded AI briefing assistant.
Baylor Journalism Quote Game
Journalism Class • Baylor University • Spring 2026
Do You Know Quotes?
Class Edition
A newspaper-themed interactive quote-matching game built for a Baylor journalism class. Players are shown a quote and must identify which classmate said it — styled as a vintage broadsheet with a masthead, section rules, and full scoring system. Built entirely in HTML, CSS, and vanilla JavaScript with no dependencies.
The engineering projects
Built in Python across five project types — agentic AI, no-code orchestration, media generation, machine learning, and full-stack web development.
Automation • Spring 2026
n8n Multi-Agent Orchestrator
11-node n8n workflow routing handyman jobs through 4 specialised AI agents — intake, pricing, scheduling, and communications — then sends a formatted Gmail summary. Zero lines of code.
AI Agent • Spring 2026
LangChain HandyMan Booking Agent
A ReAct-loop AI agent that books handyman jobs end-to-end — classifying requests, reading live Google Calendar availability, pricing by task type, and scheduling with confirmation. Six specialised tools wired together in a single reasoning loop.
AI Video • Spring 2026
Cinematic AI Video — Google Veo
A 15-second cinematic shot generated entirely with Google Veo and AI Studio — prompted, iterated, and directed frame-by-frame. Explores what AI-native filmmaking looks like when the model is the camera operator.
Machine Learning • Spring 2026
Classification & Regression with scikit-learn
Iris flower classifier hitting 96% accuracy using four scikit-learn models — Logistic Regression, Decision Tree, Random Forest, and KNN — with a full EDA pipeline, confusion matrices, and cross-validation comparison.
Full-Stack Web • Spring 2026
Campus SkillSwap Marketplace
A full-stack Django marketplace where students list skills they can teach and request skills they want to learn — user auth, profiles, listing creation, and a browse/filter system. Deployed and running end-to-end.
NLP • 4V98 • Spring 2026
Python Chatbot — AI: Principles and Application
The class project where it all started — a terminal chatbot built from scratch with the Gemini API, manual conversation history management, and a purpose-built system prompt. The foundation for every AI interface in this portfolio.