Suraj Rampure
Lecturer III
Computer Science and Engineering, University of Michigan
rampure@umich.edu
Hi! 👋 I’m Suraj (“soo-rudge”), a teaching faculty member in Computer Science and Engineering at the University of Michigan, affiliated with MIDAS. This year, I’m teaching a new class on practical data science and serving on the undergraduate data science program committee.
Previously, I spent three years as a lecturer 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 🇨🇦.
Below, you’ll find public course websites for most of the classes I’ve taught, along with my scholarly work. In addition:
- If you’re interested in applying to teaching faculty positions, access my CV, teaching statement, and the rest of my application materials here. I’ve updated this in 2024 to include my latest materials.
- If you’re thinking of asking me to write a recommendation letter for you, read this first.
- If you’re looking for datasets to use in projects of your own, look here.
Teaching
At the University of Michigan (2024-)
EECS 398-003: Practical Data Science 🛠️
Winter 2025 • Fall 2024
Highlights: Linear Algebra Review for Data Science (LARDS)
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
Highlights: Regression FAQs, Past Exam Practice
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
Highlights: Past Exam Practice
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)
Highlights: Past Exam Practice
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)
Panels
- 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)
Other
- Interview for Computing Paths @ UCSD (video)
- UC Berkeley Data Science Education Podcast Guest (“The Importance of Data Science Course Staff”) (episode link)
- 2020 EECS/CS Student Life Panel Moderator (video)
Awards
- 2023-2024 UC San Diego Distinguished Teaching Award
- 2020-2021 UC Berkeley Extraordinary Teaching in Extraordinary Times Award (article)
- 2019-2020 UC Berkeley EECS Distinguished GSI Award
- 2017-2018 UC Berkeley EECS Outstanding GSI Award
What do you think happened here?