Noah Serrault
Studying data science at UW–Madison.
Building software and making sense of data.
Things I’m working on
DIFY Battery
A platform for mobile battery service: quoting, dispatch, payments, and a technician app built for work in the field.
As the sole developer, I’m building the web platform and mobile app to support preparations for DIFY’s Phoenix launch.
- AI-assisted quoting with 12,000+ vehicle-to-battery fitment records.
- Payment reconciliation, inventory updates, and warranty creation.
- Encrypted offline queues that retain technician updates during network interruptions.
Geospatial market analysis
Combining battery-service records with Census data to understand pricing patterns and explore potential expansion markets.
I used weighted and geographically weighted regression, spatial autocorrelation tests, and held-out markets to evaluate how well demand models transfer to new places.
A little experience
Wisconsin Grocers Association
Data Analyst Intern · May–July 2025
Maintained customer records in Excel and analyzed underserved segments and potential customer bases for marketing campaigns.
DIFY Battery · Austin
Lead Technician · Self-employed
Launched the Austin market and grew monthly sales from $0 to $40K+, managing service requests, installations, scheduling, and inventory. Trained the incoming technician.
What I’m learning
B.S. Data Science · Computer Science certificate
Relevant coursework
A closer look at the topics and coursework. Fall 2026 coverage includes planned topics.
Data Science Modeling I
- R & RStudio, vectors and data frames
- Exploratory analysis, descriptive statistics and visualization
- Data cleaning and transformation with dplyr
- Probability, sampling and inference for means, proportions and regression
Data Science Modeling II
- Probability, random variables and the central limit theorem
- Monte Carlo simulation, estimation and hypothesis testing
- Linear, multiple and logistic regression
- Bootstrapping, model selection and cross-validation
Machine Learning
Fall 2026 · in progress / planned coverage
- K-nearest neighbors, Naive Bayes, decision trees and linear models
- Neural networks, support vector machines and optimization
- Clustering, dimensionality reduction and self-supervised learning
- Model evaluation, ensembles, link analysis and language modeling
Advanced Quantitative Analysis
- Statistical and spatial analysis in R
- Multiple regression, spatial autoregression and geographically weighted regression
- Bayesian inference, categorical prediction, SVMs and decision trees
- Multivariate methods, principal components and time series
Artificial Intelligence
Fall 2026 · in progress / planned coverage
- Probability, linear algebra, PCA and natural language processing
- Clustering, classification and regression
- Neural networks, deep learning and generative models
- Search, games, reinforcement learning and AI ethics
Programming III
- Binary search trees, rotations, red-black trees, AVL trees and B-trees
- Graphs, minimum spanning trees and shortest paths
- Sorting, hash tables, tries and skip lists
- Bash, JUnit, Git, SSH, Make, code review and integration
- Lambda expressions, HTML/CSS, JavaScript, web servers, JavaFX and regular expressions
Programming II
- Object-oriented design, interfaces, generics and exception handling
- Lists, stacks, queues, heaps and binary search trees
- Recursion, searching, sorting and complexity analysis
- Iterators, file I/O and testing boundary conditions
Data Management for Data Science
Fall 2026 · in progress / planned coverage
- Linux, Docker, relational databases, SQL joins, subqueries and window functions
- MongoDB, geospatial queries, Elasticsearch and Kibana
- Data ingestion, ELT pipelines, dbt, modeling and normalization
- EDA, time series, imputation, resampling and feature engineering
- Gradient boosting, LLaMA fine-tuning, retrieval-augmented generation and data storytelling
Building User Interfaces
Fall 2026 · in progress / planned coverage
- Web, mobile and conversational interfaces
- React, React Native and event-driven interaction
- Design thinking, visual design, accessibility and prototyping
- Expert evaluation, usability testing and secure interfaces
Also around: Agentic AI UW, dotData, cycling & triathlon.