Data Science Boot Camp
Summer 2025
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Registration Deadlines
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All Erdős Summer 2025 Career Launch Cohort or Alumni Club members who are not participating in the UX Research nor Deep Learning Boot Camps
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Category
Launch, Core Program, Boot Camp, Projects, Certificates
Overview
The Erdős Institute's signature Data Science Boot Camp has been running since May 2018 thanks to the generous support of our sponsors, members, and partners. Due to its popularity, we now offer our boot camp online three times per year in two different formats: a 1-month long intensive boot camp each May and a semester long version each Spring & Fall.

Click here to be invited to the slack organization: The Erdős Institute
Click here to access the slack channel: #slack-channel
Organizers, Instructors, and Advisors
Objectives
The goal of our Data Science Boot Camp is to provide you with the skills and mentorship necessary to produce a portfolio worthy data science/machine learning project while also providing you with valuable career development support and connecting you with potential employers.
Project Examples
TEAM 5
Predicting Problematic Internet Use
Daniel Visscher, Emilie Wiesner, Aaron Weinberg




Internet use has been identified by researchers as having the potential to rise to the level of addiction, with associated increased rates of anxiety and depression. Identifying cases of problematic internet usage currently requires evaluation by an expert, however, which is a significant impediment to screening children and adolescents across society. One potential solution is to rely on data that is more easily and uniformly collected: the kind collected by a family physician, a simple survey, or by a smartwatch. The research question this project sets out to answer is: “Can we predict the level of problematic internet usage exhibited by children and adolescents, based on their physical activity and survey responses?”
TEAM 26
Continuous Glucose Monitoring
Daniel Visscher,Margaret Swerdloff,Noah Gillespie,S. C. Park,oladimeji olaluwoye




The idea of the project is to predict high glucose spikes from continuous glucose data, smartwatch data, food logs, and glycemic index. The dataset consists of the following:
1) Tri-axial accelerometer data (movement in subject)
2) Blood volume pulse
3) Intestinal glucose concentration
4) Electrodermal activity
5) Heart rate
6) IBI (interbeat interval)
7) Skin temperature
8) Food log
Data is public in: https://physionet.org/content/big-ideas-glycemic-wearable/1.1.2/#files-panel
First Steps/Prerequisites
- Cloned the GitHub repo locally
- Installed the conda environment.
- Run a Jupyter Notebook using that conda environment.
- Base level familiarity with Python
- Differential calculus. Ideally you also know some multivariate differential calculus and linear algebra.
- Basic statistics and probability
Program Content
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Course materials are available on github through the following link:
github message for user
Textbook/Notes
Project/Homework Instructions
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Schedule
Click on any date for more details
Please check your registration email for program schedule and zoom links.
Project/Homework Deadlines