Data Science Boot Camp
Fall 2023
Sep 7, 2023
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Dec 7, 2023
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Registration Deadlines
Oct 1, 2023
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Academics from Member Institutions/Departments
Sep 30, 2023
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Academics from Non-Member Institutions paying the $500 cohort membership fee
Sep 30, 2023
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Academics from Non-Member Institutions applying for Corporate Sponsored Fellowships
Category
Launch
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 twice per year in two different formats: a 1-month long intensive boot camp each May and a semester long version each Fall.
Click here to be invited to the slack organization: The Erdős Institute
Click here to access the slack cohort channel: #slack-cohort-channel
Click here to access the slack program channel: #slack-program-channel
Click here to download the Events & Deadlines .ics calendar file
Organizers, Instructors, and Advisors
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!
Matthew Osborne, PhD
Lead Instructor, Senior Operations Analyst
Office Hours:
By appointment only
Email:
Preferred Contact:
Slack
Don't hesitate to contact me with any questions or concerns.
Steven Gubkin, PhD
Lead Teaching Assistant
Office Hours:
Tu: 11am - 12pm ET
Email:
Preferred Contact:
Slack
Please feel free to message me on Slack with any questions! I will also be running a “math hour” every Wednesday from 11am - 12pm ET which will explore the mathematical underpinnings of the techniques covered in the previous lecture.
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 33
Tuning Up Music Highway
James O'Quinn, Yang Mo, john hurtado cadavid, Ruixuan Ding, Chilambwe Natasha Wapamenshi
Known as the most dangerous highway in Tennessee, Music Highway, the stretch of Interstate 40 between Memphis and Nashville, could use a serious tuning up. This project investigates the effectiveness and cost-efficiency of potential physical safety interventions along its Madison and Henderson County segments, with the goal of reducing crash severity. We used a data-driven geospatial modeling approach to assess whether adding specific safety features to targeted segments predicts statistically significant changes in crash injury outcomes.
TEAM 29
Who Regulates the Regulators?
Jared Able, Joshua Jackson, Zachary Brennan, Alexandria Wheeler, Nicholas Geiser
With recent major cuts to governmental regulation agencies in the US, we investigate whether those cuts are justified. In particular, we analyze the efficacy of RGGI, a state-level cap-and-trade program designed to regulate CO2 emissions in power plants. By using synthetic controls, we answer the counterfactual question: "how would CO2 emissions look in a world where RGGI was never enacted?".
First Steps/Prerequisites
Program Content
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Course materials are available on github through the following link:
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Textbook/Notes
Note: our video player does not support playback speed options. You can find a third party browser extension which will allow you to modify video playback speed. For example, this one works for Chrome: video-speed-controller. If you would prefer to avoid a browser extension you can manually modify the playback speed in the javascript console as well: Speed up any HTML5 video player!
Fall 2023 Math Hour - Classification I
Fall 2023 Math Hour
Steven reviews mathematical concepts behind our classification I lecture
Fall 2023 Math Hour - Classification II
Fall 2023 Math Hour
Steven reviews mathematical concepts behind our classification II lecture.
Fall 2023 Math Hour - Week 12
Fall 2023 Math Hour
Steven's last math hour of the fall 2023 boot camp.
Schedule
Click on any date for more details
Phase 1: Instruction and Project Completion
Project Review & Judging
Phase 2: Intense Interview Prep & Career Connections
Lecture 1: Introduction
Sep 7, 2023 at 09:30 PM UTC
EVENT
Office Hours 1
Sep 12, 2023 at 03:00 PM UTC
EVENT
Problem Session 2
Sep 18, 2023 at 03:00 PM UTC
EVENT
Lecture 3: Supervised Learning and Regression I
Sep 21, 2023 at 09:30 PM UTC
EVENT
Math Hour 3
Sep 27, 2023 at 03:00 PM UTC
EVENT
Office Hours 4
Oct 3, 2023 at 03:00 PM UTC
EVENT
Problem Session 5
Oct 9, 2023 at 03:00 PM UTC
EVENT
Lecture 6: Time Series II
Oct 12, 2023 at 09:30 PM UTC
EVENT
Math Hour 6
Oct 18, 2023 at 03:00 PM UTC
EVENT
Office Hours 7
Oct 24, 2023 at 03:00 PM UTC
EVENT
Problem Session 8
Oct 30, 2023 at 03:00 PM UTC
EVENT
Lecture 9: Classification II
Nov 2, 2023 at 09:30 PM UTC
EVENT
Math Hour 9
Nov 8, 2023 at 04:00 PM UTC
EVENT
Lecture 11: Ensemble Learning
Nov 16, 2023 at 10:30 PM UTC
EVENT
Math Hour 11
Nov 29, 2023 at 04:00 PM UTC
EVENT
Problem Session 1
Sep 11, 2023 at 03:00 PM UTC
EVENT
Math Hour 1
Sep 13, 2023 at 03:00 PM UTC
EVENT
Office Hours 2
Sep 19, 2023 at 03:00 PM UTC
EVENT
Problem Session 3
Sep 25, 2023 at 03:00 PM UTC
EVENT
Lecture 4: Regression II
Sep 28, 2023 at 09:30 PM UTC
EVENT
Math Hour 4
Oct 4, 2023 at 03:00 PM UTC
EVENT
Office Hours 5
Oct 10, 2023 at 03:00 PM UTC
EVENT
Problem Session 6
Oct 16, 2023 at 03:00 PM UTC
EVENT
Lecture 7: Time Series II
Oct 19, 2023 at 09:30 PM UTC
EVENT
Math Hour 7
Oct 25, 2023 at 03:00 PM UTC
EVENT
Office Hours 8
Oct 31, 2023 at 03:00 PM UTC
EVENT
Problem Session 9
Nov 6, 2023 at 04:00 PM UTC
EVENT
Lecture 10: Classification III
Nov 9, 2023 at 10:30 PM UTC
EVENT
Problem Session 11
Nov 27, 2023 at 04:00 PM UTC
EVENT
Lecture 12: Neural Networks
Nov 30, 2023 at 10:30 PM UTC
EVENT
Study Group
Sep 12, 2023 at 03:00 PM UTC
EVENT
Lecture 2: Data Collection
Sep 14, 2023 at 09:30 PM UTC
EVENT
Math Hour 2
Sep 20, 2023 at 03:00 PM UTC
EVENT
Office Hours 3
Sep 26, 2023 at 03:00 PM UTC
EVENT
Problem Session 4
Oct 2, 2023 at 03:00 PM UTC
EVENT
Lecture 5: Regression III & Time Series I
Oct 5, 2023 at 09:30 PM UTC
EVENT
Math Hour 5
Oct 11, 2023 at 03:00 PM UTC
EVENT
Office Hours 6
Oct 17, 2023 at 03:00 PM UTC
EVENT
Problem Session 7
Oct 23, 2023 at 03:00 PM UTC
EVENT
Lecture 8: Classification I
Oct 26, 2023 at 09:30 PM UTC
EVENT
Math Hour 8
Nov 1, 2023 at 03:00 PM UTC
EVENT
Office Hours 9
Nov 7, 2023 at 04:00 PM UTC
EVENT
Problem Session 10
Nov 13, 2023 at 04:00 PM UTC
EVENT
Office Hours 11
Nov 28, 2023 at 04:00 PM UTC
EVENT
Project Showcase and Commencement
Dec 7, 2023 at 04:55 PM UTC
EVENT
Project/Homework Deadlines
Sep 23, 2023
03:59 AM UTC
Watch 3 Previous Top Projects
Consult the project database, and watch at least 3 previous top projects from Erdos Alumni.
Oct 6, 2023
03:59 AM UTC
Watch video about Project Formation
This should help answer any Q's you may have going into project formation
Oct 6, 2023
08:30 PM UTC
Project Pitch Hour
Opportunity to meet with other Erdos Fellows and form teams and propose topics.
Oct 12, 2023
03:59 AM UTC
Submit Team Proposal or Idea to Project Formation Page
If you want to propose a project, or have an idea for a project, submit it by this date.
Oct 14, 2023
03:59 AM 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.
Oct 21, 2023
03:59 AM 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).
Oct 28, 2023
03:59 AM UTC
Data cleaning + preprocessing
Look for missing values and duplicates. Basic data manipulation & preliminary feature engineering.
Nov 4, 2023
03:59 AM UTC
Exploratory data analysis + visualizations [Checkpoint]
Distributions of variables, looking for outliers, etc. Descriptive statistics.
Nov 10, 2023
04:59 PM UTC
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).
Nov 16, 2023
04:59 AM UTC
Machine learning models or equivalent [Checkpoint]
Results with visualizations and/or metrics. List of successes and pitfalls.
Dec 2, 2023
04:59 AM UTC
Final project due
Please read the submission instructions on the link below.