Real Projects From Our Students
These aren't hypothetical examples or demo portfolios. They're actual financial models built by people who started exactly where you might be now—wondering if they could really learn this stuff.
Portfolio Performance Tracker
Completed by a student who had never opened Excel before joining our autumn 2024 program. She built this tracking system for a small investment firm in Busan.
The model pulls data from multiple sources, calculates risk metrics, and generates monthly reports automatically. It's not perfect—but it works, and that's what matters in the real world.
6 weeks
From concept to deployment
18 sheets
Connected data architecture
How Projects Actually Develop
Problem Selection
Students identify a real need—often from their current job or a business contact. We've seen everything from restaurant cash flow models to manufacturing cost analysis. The key is choosing something genuinely useful rather than academically impressive.
Building Phase
This takes 4-8 weeks typically. There's a lot of trial and error. Formulas break. Data doesn't import cleanly. That's normal. Our instructors help troubleshoot, but students do the actual building work.
Testing Reality
Students present to the actual stakeholder—their boss, a client, whoever will use this. Feedback is often blunt. Models get revised multiple times based on how they perform with real data and real users.
Deployment
The model goes live. Some students stay involved with maintenance and updates. Others hand it off with documentation. Either way, seeing something you built actually being used daily is a different feeling than submitting coursework for a grade.
Students Behind The Work
Hwan-seok
Inventory Forecasting Model
Background in logistics, zero finance training. Built a seasonal demand forecasting tool that his company now uses for procurement planning. He says the hardest part wasn't the formulas—it was getting buy-in from managers who didn't trust spreadsheets.
Chae-rim
Budget Variance Analysis
Works at a nonprofit in Daegu. Created a grant tracking and variance reporting system because their previous method involved email chains and post-it notes. Her model cuts monthly reporting time from three days to about four hours.
Common Challenges Students Face
Building something real always involves hitting walls. Here's what typically goes wrong and how students work through it.
Data Import Problems
The Challenge
Company systems export data in formats that Excel hates. Date formats are inconsistent. Numbers come through as text. Headers change randomly between exports.
What Works
Power Query becomes your friend here. Students learn to build import processes that clean and standardize data automatically. It takes time to set up initially, but then it runs smoothly for months.
- Create standardized import templates that force consistent formatting
- Use data validation to catch problems before they break formulas
- Build error-checking sheets that flag anomalies for manual review
Scope Creep
The Challenge
Projects start simple. Then stakeholders ask "can it also do this?" repeatedly. Before you know it, you're building something way beyond the original plan.
What Works
Version discipline. Build the core functionality first and get it working reliably. Document additional requests for version 2.0. Some features that seemed critical in discussions turn out unnecessary once the basic model is running.
- Define minimum viable product clearly before starting
- Track feature requests separately from core requirements
- Plan for iterative releases rather than one massive launch
Performance Issues
The Challenge
Models work fine with test data. Then real datasets make them crawl. Calculations take minutes. Files crash when multiple people open them.
What Works
Optimization isn't glamorous but it matters. Students learn to use tables instead of ranges, replace volatile functions with static alternatives, and separate data storage from calculation sheets. Sometimes the solution is splitting one massive file into linked workbooks.
- Minimize use of INDIRECT, OFFSET, and other volatile functions
- Convert formulas to values once calculations are finalized
- Use manual calculation mode for large models
- Consider moving to Access or Power BI when Excel truly can't handle the scale