Students arrive at IDEEE work with uneven math and computing backgrounds. This annual one-week bootcamp reviews the mathematics IDEEE work depends on and sets up good computing habits, so everyone starts coursework and research on common ground. It is open to anyone in any of the programs who wants a refresher and is strongly recommended for incoming masters and PhD students.
Draft proposal. This is an early sketch of a proposed short course. The course number, dates, fees, and daily schedule are placeholders and will be settled before the course is first offered.
Overview
IDE xxx (proposed) is a non-credit, one-week bootcamp offered once a year. Mornings review the mathematics needed to read the modeling pages, and afternoons are hands-on labs that build good computing habits and introduce the main tools. The goal is to level the field before coursework and research begin.
This bootcamp does not replace the IDEEE Research Seminar and Journal Club. That is a separate, recurring, credit-bearing course. The two serve different purposes: this bootcamp is a one-week refresher of math and computing skills, while the seminar and journal club run through the term.
By the end of the bootcamp, participants will be able to:
- Read and use functions, derivatives, integrals, and basic matrix algebra
- Reason about probability and common distributions
- Work in a plain-text scientific workflow
- Organize a project, its data, and its file paths
- Get started in R, Python, and Julia
- Track their work with version control in Git
Who should apply
The bootcamp is open to participants at all tiers who want a refresher, and it is strongly recommended for incoming masters and PhD students.
Prerequisites. None. The bootcamp assumes no prior math beyond high school and no prior programming experience.
Format and delivery
- Duration. 1 week (5 days), intensive, offered annually.
- Mode. Hybrid. Attend in person or join online.
- Daily hours. A morning concept review and an afternoon hands-on lab, roughly a full working day.
- Assessment. No formal assessment.
- Certificate. Participants who attend receive a certificate of attendance.
- Equipment. Participants bring their own laptops. Instructions for installing R, Python, Julia, and Git are sent before the bootcamp begins.
Course content and topics
Math you need
- Functions and graphs
- Derivatives and the chain rule
- Integrals
- A little linear algebra: matrices and eigenvalues
- Probability and distributions
Good programming practices
- Plain-text workflows and why they matter
- Storing and organizing data
- A review of the file system and paths
- Project structure
Tooling basics
- Getting started in R, Python, and Julia, side by side
- Version control with Git
Day-by-day timetable
| Day | Morning concept review | Afternoon lab |
|---|---|---|
| 1 | Functions, graphs, and distributions | Getting started: R, Python, and Julia side by side |
| 2 | Derivatives and the chain rule | Plain-text workflows, file systems, and paths |
| 3 | Integrals | Storing and organizing data; project structure |
| 4 | Matrices and eigenvalues | Version control with Git |
| 5 | Probability and distributions | Putting it together: a small reproducible project |
Site resources
The bootcamp draws on material already published on this site. Participants can read ahead or review afterward.
Math foundations
- Functions and graphs
- Derivatives
- The chain rule
- Integrals
- Matrix operations
- Eigenvalues and eigenvectors
- Probability basics
- Distributions overview
Computing
- Computer basics
- Good programming practices
- Project workflow
- Data representation and formats
- Version control with Git
A further page on plain-text workflows and file-system orientation is planned and will be linked here once published.
See Programs for how this bootcamp fits alongside the degree tracks and other offerings.
Fees and how to apply
Fees. @placeholder
How to apply. @placeholder
AI and academic integrity
Large language models such as ChatGPT, Claude, and Gemini can support your learning, and you are welcome to use them. If you do, cite the tools you used and describe how you used them. These tools do not replace your own understanding of the material, and you remain responsible for the accuracy of your work and any citations. Using them without attribution is plagiarism.
Proposal change notice
This is a draft proposal. Its content, structure, dates, and fees are subject to change before the course is offered.