Data Science Boot Camp
Spring 2025
Jan 23, 2025
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Apr 30, 2025

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Registration Deadlines
Jan 29, 2025
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All Erdős Spring 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.
Our goal is to provide you with the skills and mentorship necessary to produce a portfolio worthy data science project.
We will learn the fundamentals of data science including: data collection, data cleaning, exploratory data analysis, inferential statistics, supervised and unsupervised machine learning techniques, and the basics of neural networks.
Each week of the course we will have a live lecture, a problem session, and an optional "math hour" and office hour.
In order to receive a Data Science certificate you must complete a portfolio worthy project in collaboration with a team of your peers.

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
Steven Gubkin, PhD
Lead Instructor
Office Hours:
W 11am - 12pm and by appt.
Email:
Preferred Contact:
Slack
Please feel free to message me on Slack with any questions!
Alec Clott, PhD
Head of Data Science Projects
Office Hours:
By appt. only
Email:
Preferred Contact:
Slack
Participants are welcome to reach out to me via slack or email. I normally work standard EST hours (9am-5pm), but can always find time to meet folks via Zoom too after work. Let me know how I can help!
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
DSBC Orientation
Live Lectures
Cohort Orientation.
Project/Homework Instructions
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Schedule
Click on any date for more details
DS Bootcamp computer setup day
Jan 23, 2025 at 07:00 PM UTC
EVENT
Office Hour 01
Jan 29, 2025 at 04:00 PM UTC
EVENT
Math Hour 02
Feb 5, 2025 at 03:00 PM UTC
EVENT
Lecture 03: Regression II
Feb 11, 2025 at 05:00 PM UTC
EVENT
Problem Session 03
Feb 13, 2025 at 07:00 PM UTC
EVENT
Math Hour 04
Feb 19, 2025 at 03:00 PM UTC
EVENT
Lecture 05: Inference I
Feb 25, 2025 at 05:00 PM UTC
EVENT
Problem Session 05
Feb 27, 2025 at 07:00 PM UTC
EVENT
Office Hour 06
Mar 5, 2025 at 04:00 PM UTC
EVENT
Math Hour 07
Mar 12, 2025 at 03:00 PM UTC
EVENT
Lecture 08: Classification I
Mar 18, 2025 at 05:00 PM UTC
EVENT
Problem Session 08
Mar 20, 2025 at 07:00 PM UTC
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Office Hour 09
Mar 26, 2025 at 04:00 PM UTC
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Math Hour 10
Apr 2, 2025 at 03:00 PM UTC
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Lecture 11: Ensemble Learning II
Apr 8, 2025 at 05:00 PM UTC
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Problem Session 11
Apr 10, 2025 at 07:00 PM UTC
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Office Hour 12
Apr 16, 2025 at 04:00 PM UTC
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Lecture 01: Introduction, Computer Setup, Q/A
Jan 28, 2025 at 05:00 PM UTC
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Problem Session 01
Jan 30, 2025 at 07:00 PM UTC
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Office Hour 02
Feb 5, 2025 at 04:00 PM UTC
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Math Hour 03
Feb 12, 2025 at 03:00 PM UTC
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Project Pitch Hour
Feb 17, 2025 at 10:00 PM UTC
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Office Hour 04
Feb 19, 2025 at 04:00 PM UTC
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Math Hour 05
Feb 26, 2025 at 03:00 PM UTC
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Lecture 06: Inference II
Mar 4, 2025 at 05:00 PM UTC
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Problem Session 06
Mar 6, 2025 at 07:00 PM UTC
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Office Hour 07
Mar 12, 2025 at 04:00 PM UTC
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Math Hour 08
Mar 19, 2025 at 03:00 PM UTC
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Lecture 09: Classification II
Mar 25, 2025 at 05:00 PM UTC
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Problem Session 09
Mar 27, 2025 at 07:00 PM UTC
EVENT
Office Hour 10
Apr 2, 2025 at 04:00 PM UTC
EVENT
Math Hour 11
Apr 9, 2025 at 03:00 PM UTC
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Lecture 12: Introduction to Neural Networks
Apr 15, 2025 at 05:00 PM UTC
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Problem Session 12
Apr 24, 2025 at 06:00 PM UTC
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Math Hour 01
Jan 29, 2025 at 03:00 PM UTC
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Lecture 02: Regression I
Feb 4, 2025 at 05:00 PM UTC
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Problem Session 02
Feb 6, 2025 at 07:00 PM UTC
EVENT
Office Hour 03
Feb 12, 2025 at 04:00 PM UTC
EVENT
Lecture 04: Regression III
Feb 18, 2025 at 05:00 PM UTC
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Problem Session 04
Feb 20, 2025 at 07:00 PM UTC
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Office Hour 05
Feb 26, 2025 at 04:00 PM UTC
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Math Hour 06
Mar 5, 2025 at 03:00 PM UTC
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Lecture 07: Time Series
Mar 11, 2025 at 05:00 PM UTC
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Problem Session 07
Mar 13, 2025 at 07:00 PM UTC
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Office Hour 08
Mar 19, 2025 at 04:00 PM UTC
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Math Hour 09
Mar 26, 2025 at 03:00 PM UTC
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Lecture 10: Ensemble Learning I
Apr 1, 2025 at 05:00 PM UTC
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Problem Session 10
Apr 3, 2025 at 07:00 PM UTC
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Office Hour 11
Apr 9, 2025 at 04:00 PM UTC
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Math Hour 12
Apr 16, 2025 at 03:00 PM UTC
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Commencement and Project Showcase
Apr 30, 2025 at 04:00 PM UTC
EVENT
Please check your registration email for program schedule and zoom links.
Project/Homework Deadlines
Feb 7, 2025
04:59 PM UTC
Watch video about Project Formation
This should help answer any Q's you may have going into project formation
Feb 7, 2025
04:59 PM UTC
Watch 3 Previous Top Projects
Consult the project database, and watch at least 3 previous top projects from Erdos Alumni.
Feb 17, 2025
10:00 PM UTC
Project Pitch Hour
Opportunity to meet with other Erdos Fellows and form teams and propose topics.
Feb 21, 2025
04:59 PM UTC
Finalized Teams with Preliminary Project Ideas
Teams need to be finalized by this point. If you proposed or created a project, you must have others in your group. If you did not propose or create a project, you must join an open group.
Feb 21, 2025
04:59 PM UTC
Data gathering and defining stakeholders + KPIs
Find the dataset you will be working with. Describe the dataset and the problem you are looking to solve (1 page max). List the stakeholders of the project and company key performance indicators (KPIs) (bullet points).
Mar 7, 2025
04:59 PM UTC
Exploratory data analysis + visualizations [Checkpoint]
Distributions of variables, looking for outliers, etc. Descriptive statistics.
Mar 7, 2025
04:59 PM UTC
Data cleaning + preprocessing
Look for missing values and duplicates. Basic data manipulation & preliminary feature engineering.
Mar 22, 2025
03:59 AM UTC
Written proposal of modeling approach [Checkpoint]
Describe your planned modeling approach, based on the exploratory data analysis from the last two weeks (< 1 page, bullet points).
Mar 29, 2025
03:59 AM UTC
Machine learning models or equivalent [Checkpoint]
Results with visualizations and/or metrics. List of successes and pitfalls.
Apr 22, 2025
03:59 AM UTC
Final Projects Due
Final Projects must be submitted by this deadline in order to receive a certificate of completion.