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Data Science Boot Camp

May-Summer 2024

May 6, 2024

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Jun 5, 2024

Register

You are registered for this program.

Registration Deadlines

May 6, 2024

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All interested participants

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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.

Organizers and Instructors

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Steven Gubkin, PhD

Lead Instructor

Office Hours:

MTWRF 12pm - 1pm ET, and by appt.

Email:

Preferred Contact:

Slack

Please feel free to message me on Slack with any questions!

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Alec Clott, PhD

Head of Data Science Projects

Office Hours:

Wed. 12-12:30pm EST, and by appt.

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.

Slack

Slack Channel: #slack-channel

Project Examples

TEAM

Groundwater Forecasting

Riti Bahl, Meredith Sargent, Marcos Ortiz, Chelsea Gary, Anireju Dudun

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github URL

Groundwater is a critical source of water human survival. A significant percentage of both drinking and crop irrigation water is drawn from groundwater sources through wells. In the US, overuse of groundwater could have major implications for the future and forecasting groundwater can be useful in understanding its impact. Building on historical data for four wells, together with surface water and weather data, in Spokane, WA, we construct and evaluate machine learning models that forecast groundwater levels in the area.

TEAM

Correcting Racial Bias in Measurement of Blood Oxygen Saturation

Rohan Myers, Saad Khalid, woojeong kim, Brooks Miner, Jaychandran Padayasi

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github URL

Fingertip pulse oximeters are the current standard for estimating blood oxygen saturation without a blood draw, both at home and in healthcare settings. However, pulse oximeters overestimate oxygen saturation, often resulting in ‘hidden hypoxemia’: a patient has hypoxemia (dangerously low oxygen saturation), but the oximeter returns a healthy oxygen value. Unfortunately, oximeter overestimation of oxygen saturation is exacerbated for patients with darker skin tones due to light-based oximeter technology. This results in Black patients experiencing hidden hypoxemia at twice the rate of white patients. By combining pulse oximeter readings (SpO2) with additional patient data, we develop improved methods for estimating arterial blood oxygen saturation (SaO2) and identifying Hidden Hypoxemia. The predictions of our models are more accurate than pulse-oximeter readings alone, and remove the systematic racial inequity inherent in the current medical practice of using oximeter readings alone.

First Steps/Prerequisites

Participants should have a base-level familiarity with Python. Participants should also be familiar with some basic math concepts. Finally, you will also need to have your laptop or desktop computer set up for the course. If you are new to Python, need a quick math refresher, or if you need help setting up your computer, then please follow the link below.

Program Content

You will find all of the course content below in our GitHub repository. If you see a 404 Error when trying to open this repository, first check that you are signed into your GitHub account and then check with our community manager that you have been added to our repositories. Because our repositories are private, you must first be added before you can access them.

 

Every week has a collection of pre-recorded videos: one for each notebook in the repo.

 

Recordings of each live lecture will be posted by 10am the following day.

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Program Content

Textbook/Notes

How to clone the GitHub Repo

Technical Support

This video will walk you through cloning the GitHub repo. It also addresses how to troubleshoot some common pitfalls.

Transcript
Code

Project/Homework Instructions

Erdős Project Instructions (May-Summer 2024)

The group project is a time to put everything you’ve learned to the test! You will work with your team to produce a portfolio-worthy project that you can use as a talking point with future employers.

 

General Information

In order to get an Erdős certificate, you must complete a data science project from start to finish.

 

Project Topics

Your project can be anything you would like, as long as you use Python. We want your project to be something you’re passionate about and can really dig into. We understand that open ended projects can be difficult so we’ve provided a few resources:

Possible project list

General advice

Project Database (Past Project Examples)

 

Project Help

There are a number of Project Mentors that will be available for project help! Feel free to chat with them via Slack (#project-help) for advice.

 

Project Expectations

The goal is to complete a data science project that could be presented in a job interview.

 

3 Deliverable Requirements (see more details below)

Have an annotated GitHub repository

Executive summary of your project results and implications

5-min pre-recorded PowerPoint presentation detailing project process from start to finish

 

Timeline

The tasks for each week should be submitted to your Project Mentor before your weekly check-in. Some of the items listed below are more of a rough guideline, depending on your project. Consult your project mentor or Alec if you are unsure.

 

Questions about Project Formation:

Please watch the following video, it should help answer any questions you may have about project formation.

 

Project Pitch Hour:

Each session we will hold a "Project Pitch Hour" for everyone to join via Zoom. See the "Schedule" above. The Project Pitch Hour will be an opportunity for anyone without a team to join on Zoom. Once on Zoom, we will give folks an opportunity to "pitch" a project and see who else is interested. In other words, if you join the Project Pitch Hour be ready to fall in one of the two following camps:

 

1. You have a project idea you want to pitch, and are hoping to get other people to join.

2. You don't have a project idea, but you want to see what others are pitching and are hoping to join someone elses team.

 

If you are in camp (1), your pitch can last from anywhere between 30 seconds to 2-3 minutes. There is no expectation to make a formal presentation or in-depth pitch. Your pitch ould be as simple as "I want to do a project on sports, but don't know the methodology yet!" or "I've already identified the exact dataset I want to use, and a few ideas on methodology but am looking for a team." In other words - as basic or as detailed as you like.

 

If you are in camp (2), come with an open mind and be willing to ask questions! And of course, be willing to go in a direction you might not have considered previously!

Project/Team Formation
Project Submission
Projects README

How To Form Projects

Presentation Tips and Tricks (prerecorded)

This video should show you how to navigate the team formation process on the Erdos website.

Slides
Transcript

Schedule

Click on any date for more details

Problem Solving Session 1

May 6, 2024 at 3:00:00 PM

EVENT

Problem Solving Session 2

May 7, 2024 at 3:00:00 PM

EVENT

Problem Solving Session 3

May 8, 2024 at 3:00:00 PM

EVENT

Problem Solving Session 4

May 9, 2024 at 3:00:00 PM

EVENT

Project Pitch Hour

May 10, 2024 at 4:00:00 PM

EVENT

Lecture 5: Regression III

May 13, 2024 at 7:00:00 PM

EVENT

Lecture 6: Time Series I

May 14, 2024 at 7:00:00 PM

EVENT

Lecture 7: Time Series II

May 15, 2024 at 7:00:00 PM

EVENT

Lecture 8: Classification I

May 16, 2024 at 7:00:00 PM

EVENT

Office Hours

May 20, 2024 at 4:00:00 PM

EVENT

Office Hours

May 21, 2024 at 4:00:00 PM

EVENT

Office Hours

May 22, 2024 at 4:00:00 PM

EVENT

Office Hours

May 23, 2024 at 4:00:00 PM

EVENT

Office Hours

May 24, 2024 at 4:00:00 PM

EVENT

Office Hours

May 29, 2024 at 4:00:00 PM

EVENT

Office Hours

May 6, 2024 at 4:00:00 PM

EVENT

Office Hours

May 7, 2024 at 4:00:00 PM

EVENT

Office Hours

May 8, 2024 at 4:00:00 PM

EVENT

Office Hours

May 9, 2024 at 4:00:00 PM

EVENT

Problem Solving Session 5

May 13, 2024 at 3:00:00 PM

EVENT

Problem Solving Session 6

May 14, 2024 at 3:00:00 PM

EVENT

Problem Solving Session 7

May 15, 2024 at 3:00:00 PM

EVENT

Problem Solving Session 8

May 16, 2024 at 3:00:00 PM

EVENT

Office Hours

May 17, 2024 at 4:00:00 PM

EVENT

Lecture 9: Classification II

May 20, 2024 at 7:00:00 PM

EVENT

Lecture 10: Ensemble Learning I

May 21, 2024 at 7:00:00 PM

EVENT

Lecture 11: Ensemble Learning II

May 22, 2024 at 7:00:00 PM

EVENT

Lecture 12: Neural Networks

May 23, 2024 at 7:00:00 PM

EVENT

Office Hours

May 27, 2024 at 4:00:00 PM

EVENT

Office Hours

May 30, 2024 at 4:00:00 PM

EVENT

Lecture 1: Introduction

May 6, 2024 at 7:00:00 PM

EVENT

Lecture 2: Data Collection

May 7, 2024 at 7:00:00 PM

EVENT

Lecture 3: Regression I

May 8, 2024 at 7:00:00 PM

EVENT

Lecture 4: Regression II

May 9, 2024 at 7:00:00 PM

EVENT

Office Hours

May 13, 2024 at 4:00:00 PM

EVENT

Office Hours

May 14, 2024 at 4:00:00 PM

EVENT

Office Hours

May 15, 2024 at 4:00:00 PM

EVENT

Office Hours

May 16, 2024 at 4:00:00 PM

EVENT

Problem Solving Session 9

May 20, 2024 at 3:00:00 PM

EVENT

Problem Solving Session 10

May 21, 2024 at 3:00:00 PM

EVENT

Problem Solving Session 11

May 22, 2024 at 3:00:00 PM

EVENT

Problem Solving Session 12

May 23, 2024 at 3:00:00 PM

EVENT

Problem Solving Session 13

May 24, 2024 at 3:00:00 PM

EVENT

Office Hours

May 28, 2024 at 4:00:00 PM

EVENT

Office Hours

May 31, 2024 at 4:00:00 PM

EVENT

Please check your registration email for program schedule and zoom links.

Project/Homework Deadlines

May 11, 2024

3:59 AM

Submit Team Proposal to Project Formation Page

If you want to propose a project, or have an idea for a project, submit it by this date.

May 13, 2024

3:59 AM

Finalized Teams with Preliminary Project Idea

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.

May 17, 2024

2:06 PM

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).

May 18, 2024

3:59 AM

Data cleaning + preprocessing

Look for missing values and duplicates. Basic data manipulation & preliminary feature engineering.

May 25, 2024

3:59 AM

Written proposal of modeling approach [Checkpoint]

Test linearity assumptions. Dimensionality reductions (if necessary). Describe your planned modeling approach, based on the exploratory data analysis from the last two weeks (< 1 page, bullet points).

May 25, 2024

3:59 AM

Exploratory data analysis + visualizations [Checkpoint]

Distributions of variables, looking for outliers, etc. Descriptive statistics.

Jun 1, 2024

3:59 AM

Machine learning models or equivalent [Checkpoint]

Results with visualizations and/or metrics. List of successes and pitfalls.

Jun 2, 2024

3:59 AM

Final project due

Please read the submission instructions on the link below.

To access the program content, you must first create an account and member profile and be logged in.

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