3 Projects We Love from Flatiron School’s Global Final Project Showcase

Table of Contents

• 1. “FatKat”
• 2. “DundieHub”
• 3. “ShadeSense”

Capstone projects are one cornerstone of a reputable, immersive technical bootcamp; oftentimes, students take the opportunity to get creative and build something they’re passionate about. We recently tuned into the Global Final Project Showcase at Flatiron School, and were particularly impressed with three projects created by Software Engineering and Data Science Bootcamp students. Be sure to click-through to these students’ GitHub repositories to get a deeper look into these capstone projects, from creating unique datasets to building out creative social media applications! 

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1. “FatKat”

Before enrolling at Flatiron School’s Data Science Bootcamp: Andrei Hushcha was a data analyst. 

What does FatKat do? Andrei is creating a mobile app that utilizes neural networks to decipher and classify a cat’s meows. Through this modeling, cat owners will be able to understand if their cat is hungry, looking for attention, or feeling playful. The modeling also detects true cat sounds versus humans mimicking cat sounds. 

Tools and languages used to build FatKat: Librosa, Tensorflow, Keras, Scikit Learn, Dummy, XGBoost, Sequential Neural Network.

What inspired Andrei to learn data science now? “I’ve loved data since I was a kid. I was good at math in high school and statistics in college. Data science gives you insights and evidence based on somebody’s data that helps you improve someone's life or their business. It’s as simple as that!” 

Will Andrei be using this FatKat project in future job interviews? “We have to talk about our project because it shows our potential and our personality. You can explain your project in technical and non-technical ways, which also shows your presentation skills.”

2. “DundieHub”

Before enrolling at Flatiron School’s Software Engineering Bootcamp: Cooper Lindsley was a fundraiser for different universities and organizations.

What does DundieHub do? Cooper built a full stack web application modeled on social media apps where characters from “The Office” can interact. 

Tools and languages used to build DundieHub: CSS, Python, SQLAlchemy, Flask, React, Figma for wireframing

Why Cooper is making a career change into software engineering: “I’m a career changer, so I spent 6 years in the professional field of fundraising, which meant doing very non-technical work and using my soft skills to talk to people. As great of a job as it was, it didn’t lend itself to being very creative. Having this blank canvas to build whatever I wanted [for my final project] was just a really cool opportunity to do something I had already thought about from the beginning of this journey.”

How will Cooper be using this project after bootcamp? “These projects may be a good way to network and build community! One of the big things I’ve done in my job search is to talk with folks who have gone through non-traditional paths, such as other Flatiron School graduates, in order to find out how they got their first and second jobs. So many of them say it’s been through their networks! You’d be amazed to learn how many people know someone who knows someone who is dying to get someone with your skill set into their company. These projects are a great way to build those relationships.”

3. “ShadeSense”

Before enrolling at Flatiron School’s Data Science Bootcamp: Gina Guerin was working as a manager in the service industry.

What does ShadeSense do? Gina built an application that utilizes neural networks to identify specific shades of lipstick that someone is wearing in real-time or through an uploaded image. 

Tools and languages used to build ShadeSense: Convolutional Neural Networks (CNN), Python, machine learning

What inspired Gina to get into data science this year? “Honestly, the thing that got the ball rolling for me was back in the MySpace days when everyone was a coder. That’s where it all started because it was a place where you could see what you could create. I was in the service industry for a long time and to be able to track seasonal changes and sales got me thinking about wrangling data in data science so I could make predictions and understand the data.”

Why Gina will be using ShadeSense in her job interviews: “Being a beginner means that these projects are your work experience. We’re building these projects and using them to show [employers] that we developed something solo or collaborated with other people (which shows teamwork) or have the ability to create our own datasets.”

Find out more and read Flatiron School reviews on Course Report. This article was produced by the Course Report team in partnership with Flatiron School.