Data Science Boot Camp
Fall 2024
Sep 5, 2024
-
Dec 13, 2024
Checking your registration status...
You are registered for this program.
Registration Deadlines
Sep 6, 2024
-
All Erdős Fall 2024 Career Launch Cohort or Alumni Club members who are not participating in the UX Research nor Deep Learning Boot Camps
-
-
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.
#slack-channel
Organizers, Instructors, and Advisors
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!
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
Aware NLP Project III
Mohammad Nooranidoost, Baian Liu, Craig Franze, Mustafa Anıl Tokmak, Himanshu Raj, Peter Williams
This project involves the investigation and evaluation of different methodologies for retrieval for use in RAG (Retrieval-Augmented Generation) systems. In particular, this project investigates retrieval quality for information downloaded from employee subreddits. We investigated the impacts of using clustering, multi-vector indexing, and multi-querying in advanced retrieval methodologies against baseline naive retrieval.
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
I'm a paragraph. Click here to add your own text and edit me. It's easy.
Textbook/Notes
Schedule
Click on any date for more details
DS Bootcamp computer setup day
Next Event
EVENT
Office Hour 1
Next Event
EVENT
Math Hour 2
Next Event
EVENT
Lecture 3: Regression II
Next Event
EVENT
Problem Session 3
Next Event
EVENT
Office Hour 4
Next Event
EVENT
Math Hour 5
Next Event
EVENT
Lecture 6: Inference II
Next Event
EVENT
Problem Session 6
Next Event
EVENT
Office Hour 7
Next Event
EVENT
Math Hour 8
Next Event
EVENT
Lecture 9: Classification II
Next Event
EVENT
Problem Session 9
Next Event
EVENT
Office Hour 10
Next Event
EVENT
Math Hour 11
Next Event
EVENT
Lecture 12: Introduction to Neural Networks
Next Event
EVENT
Commencement and Project Showcase
Next Event
EVENT
Lecture 1: Introduction, Computer Setup, Q/A
Next Event
EVENT
Problem Session 1
Next Event
EVENT
Office Hour 2
Next Event
EVENT
Math Hour 3
Next Event
EVENT
Lecture 4: Regression III
Next Event
EVENT
Problem Session 4
Next Event
EVENT
Office Hour 5
Next Event
EVENT
Math Hour 6
Next Event
EVENT
Lecture 7: Time Series
Next Event
EVENT
Problem Session 7
Next Event
EVENT
Office Hour 8
Next Event
EVENT
Math Hour 9
Next Event
EVENT
Lecture 10: Ensemble Learning I
Next Event
EVENT
Problem Session 10
Next Event
EVENT
Office Hour 11
Next Event
EVENT
Math Hour 12
Next Event
EVENT
Math Hour 1
Next Event
EVENT
Lecture 2: Regression I
Next Event
EVENT
Problem Session 2
Next Event
EVENT
Office Hour 3
Next Event
EVENT
Math Hour 4
Next Event
EVENT
Lecture 5: Inference I
Next Event
EVENT
Problem Session 5
Next Event
EVENT
Office Hour 6
Next Event
EVENT
Math Hour 7
Next Event
EVENT
Lecture 8: Classification I
Next Event
EVENT
Problem Session 8
Next Event
EVENT
Office Hour 9
Next Event
EVENT
Math Hour 10
Next Event
EVENT
Lecture 11: Ensemble Learning II
Next Event
EVENT
Problem Session 11
Next Event
EVENT
Office Hour 12
Next Event
EVENT
Please check your registration email for program schedule and zoom links.
Project/Homework Deadlines
Sep 20, 2024
Next Event
Watch video about Project Formation
This should help answer any Q's you may have going into project formation
Sep 20, 2024
Next Event
Watch 3 Previous Top Projects
Consult the project database, and watch at least 3 previous top projects from Erdos Alumni.
Sep 27, 2024
Next Event
Project Pitch Hour
Opportunity to meet with other Erdos Fellows and form teams and propose topics.
Oct 4, 2024
Next Event
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 4, 2024
Next Event
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 18, 2024
Next Event
Exploratory data analysis + visualizations [Checkpoint]
Distributions of variables, looking for outliers, etc. Descriptive statistics.
Oct 18, 2024
Next Event
Data cleaning + preprocessing
Look for missing values and duplicates. Basic data manipulation & preliminary feature engineering.
Nov 1, 2024
Next Event
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).
Nov 8, 2024
Next Event
Machine learning models or equivalent [Checkpoint]
Results with visualizations and/or metrics. List of successes and pitfalls.
Dec 3, 2024
Next Event
Final Projects Due
Final Projects must be submitted by this deadline in order to receive a certificate of completion.