Home • Suraj Rampure

Suraj Rampure

Lecturer III
Computer Science and Engineering, University of Michigan
rampure@umich.edu

📍 Loading location...

Hi! 👋 I’m Suraj (“soo-rudge”), a teaching faculty member in Computer Science and Engineering at the University of Michigan. At Michigan, I am affiliated with MIDAS and serve on the undergraduate computer science and data science program committees.

Previously, I taught in the Halıcıoğlu Data Science Institute at the University of California, San Diego, where I coordinated the senior data science capstone program and received the campus-wide Distinguished Teaching Award in 2024. I earned BS and MS degrees in Electrical Engineering and Computer Sciences from the University of California, Berkeley, and I’m originally from Windsor, Ontario 🇨🇦.

On this page: Teaching • Scholarship • Awards
Other links: CV (as of June 2025) • Teaching Faculty Application Materials • Recommendation Letters • Python Teaching Commons
Totally random: Travel Recommendations

Teaching

At the University of Michigan (2024-)

EECS 298: Mathematics for Machine Learning 🧠
(Offered as EECS 245 starting in Winter 2026!)
Fall 2025

EECS 398: Practical Data Science 🛠️
Spring 2025 (Half-Term) • Winter 2025 • Fall 2024

At UC San Diego (2021-2024)

You can view course websites for many DSC (and adjacent) courses at dsc-courses.github.io.

DSC 40A: Theoretical Foundations of Data Science I 🧠
Spring 2024 • Fall 2021

DSC 95: Tutor Apprenticeship in Data Science 🧑‍🏫
Spring 2024 • Spring 2023

DSC 80: Practice and Application of Data Science 💪
Winter 2024 • Winter 2023 • Spring 2022

DSC 180AB: Data Science Project (Senior Capstone) 👷
Fall 2023 + Winter 2024 • Fall 2022 + Winter 2023

DSC 10: Principles of Data Science 📊
Fall 2023 (with Janine Tiefenbruck & Rod Albuyeh) • Spring 2023 • Fall 2022 (with Janine Tiefenbruck & Puoya Tabaghi) • Winter 2022 • Fall 2021 (with Janine Tiefenbruck)

CSS 201S: Introduction to Python Bootcamp (Week 1 only) 🥾
Summer 2022

DSC 90: History of Data Science Seminar 📚
Spring 2022 • Winter 2022

At UC Berkeley (2016-2021)

Data 94: Introduction to Computational Thinking with Data
Spring 2021 (now known as Data 6)

Data 100: Principles and Techniques of Data Science
Summer 2020 (with Allen Shen)
TA: Fall 2020 • Spring 2020 • Fall 2019 • Spring 2019 • Fall 2018

CS 198-087: Introduction to Mathematical Thinking DeCal
Spring 2019, Fall 2018

CS 70: Discrete Mathematics and Probability Theory
TA: Summer 2019

CS 375: Teaching Techniques for Computer Science
TA: Summer 2019

CS 61A: Structure and Interpretation of Computer Programs
TA: Spring 2018

Data 8: Foundations of Data Science
TA: Fall 2017
Tutor: Spring 2017

Scholarship

Papers

The Challenges of Evolving Technical Courses at Scale: Four Case Studies of Updating Large Data Science Courses. Sam Lau, Justin Eldridge, Shannon Ellis, Aaron Fraenkel, Marina Langlois, Suraj Rampure, Janine Tiefenbruck, Philip Guo. In ACM Conference on Learning @ Scale (L@S), 2022.
A New Data-Focused Introductory Programming Course. Suraj Rampure. 2021. Master’s technical report, UC Berkeley EECS.
Experiences Teaching a Large Upper-Division Data Science Course Remotely. Suraj Rampure*, Allen Shen*, and Josh Hug. 2020. In Proceedings of the 52nd ACM Technical Symposium on Computer Science Education (SIGCSE ’21). (slides) (video)

Talks

Different Mediums for Different Audiences: A Capstone Case Study. Suraj Rampure. Talk at Teaching and Evaluating Data Communication at Scale 2024. (slides) (video)
Otter-Grader: A Lightweight Solution for Creating and Grading Jupyter Notebook Assignments. Suraj Rampure, Christopher Pyles, Justin Eldridge, and Lisa Yan. Talk at Jupytercon 2023. (materials) (video)
Data 6: A New Introductory Course. Talk at 2021 National Workshop on Data Science Education. (slides) (video)
Various sessions on Data 100: Principles and Techniques of Data Science at 2020 National Workshop on Data Science Education. (pre-recorded talk) (Q&A) (workshop)

A New Class of Teaching-Track Faculty: No Ph.D. Required. Birds of a Feather session at Proceedings of the 56th ACM Technical Symposium on Computer Science Education (SIGCSE ‘25).
A New Class of Teaching-Track Faculty: No Ph.D. Required. In Proceedings of the 54th ACM Technical Symposium on Computer Science Education (SIGCSE ‘23). (slides)
Introduction to Computational Thinking with Data and Society. In 2022 National Workshop on Data Science Education.
A New Class of Teaching-Track Faculty: No Ph.D. Required. In Proceedings of the 53rd ACM Technical Symposium on Computer Science Education (SIGCSE ‘22). (slides)