Noah Andersen-Kiel
Recent Computer Science graduate on a journey to master data engineering and cloud technologies, combining academic foundations with hands-on learning to build robust data solutions.
About Me
I discovered my passion for Computer Science during my junior year after experiencing R programming in a Biostatistics course. This pivotal moment led me to switch majors, diving headfirst into the world of programming, AI, and data analysis. Since then, I've embraced every opportunity to learn new languages, frameworks, and technologies.
My academic journey has been diverse and impactful. Beyond my coursework, I've taken on leadership roles that have shaped my professional development. As a Python course teaching assistant, I helped fellow students grasp programming fundamentals. I also authored research on AI in education that was accepted to the FIE 2024 conference. My leadership experience extends to serving as president of Butler University Esports, where I managed large-scale operations, overseeing finances and coordinating communications across a network of hundreds of students, faculty, and partner organizations.
I'm particularly passionate about artificial intelligence and its implications for the future of technology. I was invited to lead a discussion with Butler University's leadership about generative AI's impact on education, sharing insights from my hands-on experience with these emerging technologies. I thrive on exploring new challenges and contributing to meaningful technological advancement.
Featured Projects
Google Cloud Data Analytics Capstone
A comprehensive data analytics project completed on Coursera. Worked with Google BigQuery for data manipulation and analysis, created SQL queries for data cleaning and aggregation, and developed interactive dashboards using Looker. Implemented various visualization techniques including filtered distributions, cross-filtering, and conditional formatting.
Case File Tracking Application
Built Flask and MongoDB platform to track case file statuses, managing 1,000+ records with automated deadline alerts. Improved data retrieval efficiency through SQL queries and user-friendly HTML/CSS interface.
Inventory Management System
Built Python-based system with SQLite and Flask, managing 10,000+ SKUs with automated alerts. Ensured 99.8% data accuracy via validation scripts; created Excel-compatible reports.
Document Management System
Developed Python-based system with SQLite to organize and validate 5,000+ legal documents, ensuring accurate data entry and compliance with formatting standards. Created Excel reports summarizing document status, streamlining stakeholder updates.