AI Data Trainer Fellow | Information Systems Student | Builder

Building AI-powered career and learning systems for students.

I design full-stack dashboards, recommendation systems, and interactive products that turn messy student workflows into clear decisions.

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Generative AI Data Analysis Full-Stack Development Information Systems Student Success

JavaScript Python FastAPI SQLite SQL Power BI GitHub Pages Render

Selected Work

Projects built around real student decisions.

Each project focuses on a specific workflow: career planning, labor market intelligence, academic resource selection, or campus-life tradeoffs.

Live Backend deployed Case study In progress

Flagship Product JavaScript + FastAPI + SQLite

Nexus AI

A student career operating system for tracking applications, certifications, projects, networking, interviews, resume notes, goals, and skill gaps.

Built a FastAPI and SQLite backend with deployed Render API support.
Designed resume coaching, career readiness analytics, onboarding, and sample recruiter workspace flows.
Created a roadmap for authentication, PostgreSQL, and AI-assisted feedback.

Proof of work CRUD API, readiness scoring, resume notes, project storage, and deployment flow.

Live App GitHub Case Study

Live Data workflow Case study GitHub

Labor Market Intelligence JS + Python + SQL

CareerLens

A career-readiness dashboard that analyzes job postings, detects demanded skills and certifications, and turns resume gaps into an application-ready plan.

Built role-based analysis for student-facing tech paths.
Added CSV pipeline and SQL schema for scalable market intelligence.
Generated priority insights, decision briefs, portfolio evidence, and application packet assets.

Proof of work Role filters, skill demand, certification signals, resume gaps, decision briefs, and application packet logic.

Live App GitHub Case Study

Live Recommendation logic Case study GitHub

Academic Decision Support HTML + CSS + JavaScript

LearnWise

An academic resource optimization platform that ranks study recommendations by urgency, topic weakness, learning preference, time, and expected ROI, then turns them into a study plan.

Built custom recommendation logic for UMBC-style course planning.
Designed academic ROI scoring to prioritize high-impact study actions.
Created strategy briefs, deadline-aware schedules, plan export, risk scoring, and resource rankings.

Proof of work Course risk scoring, study resource ranking, strategy briefs, schedule generation, and plan export.

Live App GitHub Case Study

Live Browser game Case study GitHub

Interactive Systems Java + Processing + JavaScript

15 Weeks at UMBC

A choice-based campus-life strategy game where players manage health, food, grades, money, stress, support, and career readiness through a semester.

Built meaningful tradeoff systems across seven connected student variables.
Added save/load support, achievements, multiple endings, and profile-specific events.
Converted the original Processing project into a deployable browser game.

Proof of work Decision engine, seven tracked stats, save/load, achievements, and multiple endings.

Play Game GitHub Case Study

Featured Case Study

Nexus AI: from scattered career prep to one student operating system.

Nexus AI started from a simple problem: students prepare for internships across too many disconnected places. The product turns applications, skills, projects, resume notes, networking, and deadlines into one workspace with readiness signals and next actions.

8 career modules

3 API roadmap issues

1 hosted backend

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Capabilities

What I bring into project work.

I focus on building tools that explain what matters, store useful data, and guide people toward the next action.

FastAPI + SQLite

Nexus AI: built a hosted backend for storing applications, goals, projects, contacts, and resume notes.

Data Analysis

CareerLens: converted job-posting patterns into role insights, skill demand, certification recommendations, and application-ready next steps.

Recommendation Logic

LearnWise: ranked study actions by urgency, weak topics, time available, expected academic impact, and deadline-aware schedule fit.

Interactive Systems

15 Weeks at UMBC: designed a decision engine where each action changes player stats and endings.

Deployment

Portfolio + projects: shipped browser-ready apps through GitHub Pages and hosted backend services through Render.

Product Thinking

All projects: framed student problems, built usable workflows, and connected features to resume-ready outcomes.

Resume

Current resume and profile links.

My resume highlights AI/data training, information systems coursework, full-stack project work, and deployed student-focused products.

Jason Binong Resume Updated project section with Nexus AI, CareerLens, LearnWise, and 15 Weeks at UMBC.

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Contact

Open to AI, data, software, and information systems opportunities.

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