Projects

This project is a Next.js application served by Netlify Functions. Static assets are cached for one year, while pages and API responses are cached for 60 seconds. Serverless functions located in netlify/functions/ interact with MongoDB; the admin upload endpoint verifies a secret key and validates sections before processing CSV input and writing to MongoDB.

Developed and deployed an AI-based web application for customer feedback analytics, featuring an Emotion Detection system built with Watson AI libraries. This project processed text feedback to identify specific emotions, providing valuable insights for e-commerce. Responsible for full-stack development, including Flask deployment, unit testing, and error handling.

Developed a Node.js web application to integrate with the HubSpot CRM API. This project involved creating and managing custom objects in HubSpot, implementing GET/POST routes with Express.js and Axios, and using Pug templating for the UI. Gained hands-on experience in API integration, full-stack development, and Git workflow.

The final assignment of the IBM Data Science course is the so-called "Capstone Project" in which many of the tools and methods learned throughout the recent months are applied in a self-chosen challenge around the general idea of a "Battle of Neighbourhoods", e. g. the analysis and useful preparation of data on venues in city environments. I chose the city of Sydney as a case. To pass the final assignment, creating a Jupyter Notebook with Python as the programming language and all the necessary code and comments is required, as are a blogpost or presentation and a final report.