Programming Projects: Python, Liquid/CSS/HTML, VBA, APIs - Level UP

12 Positions Available We're looking for students with solid experience in one or more of the following technology areas to tackle technology projects on our list of priorities: Python Liquid/CSS/HTML Visual Basic (VBA/ Advanced Excel Formulas/Marcos) Graph QL and/or REST API Integrations You bring solid technical experience and enthusiasm to code business solutions. We'll help you build your portfolio of coding accomplishments to talk about in future interviews. We have a pending list of interesting programing projects that we want done and will match candidates to a subset of the following priority projects.

Optimizing Event Networking with Data Science

PopIn aims to enhance networking opportunities for event hosts on platforms like Meetup.com, Eventbrite.com, and Lu.ma. The goal of this project is to determine the ideal event sizes and locations that maximize networking potential. To achieve this, learners will scrape event data from these platforms and apply data science and analytics techniques to identify patterns and insights. The project will involve data collection, cleaning, analysis, and visualization to provide actionable recommendations for event hosts. This will help PopIn tailor their tool to better serve their users and improve networking outcomes. Key tasks include: - Scraping event data from Meetup.com, Eventbrite.com, and Lu.ma. - Cleaning and preprocessing the collected data. - Applying data science techniques to analyze the data. - Visualizing the results to identify optimal event sizes and locations.

AI-Powered Digital Wellness Agent

Building upon the existing Quell App interface, this project focuses on developing an intelligent AI agent backend using Azure AI Services to empower users in managing digital habits and overcoming digital addiction. Students will design and implement an agentic workflow leveraging Azure Cognitive Services, to analyze user data and provide personalized interventions. This involves creating a sophisticated backend capable of understanding user behavior patterns, identifying triggers for excessive digital device usage, and delivering timely, supportive feedback directly within the Quell App. Learners will gain hands-on experience with Azure AI platform, agentic workflow design, and backend development for intelligent applications. The project will explore techniques for data analysis, natural language processing, and personalized recommendation systems, all within the Azure ecosystem. Deliverables include a functional AI agent backend prototype integrated with Azure AI Services, demonstrating core agentic workflows and personalized intervention logic, along with comprehensive documentation outlining the system architecture, Azure service utilization, and testing results.